Issue №38

This study presents the development of a computer vision system based on the YOLOv8 architecture to automatically determine the ships’ aspect angle in real time. The system, named Shipboard Artificial Visual Observation System (SAVOS), aims to enhance maritime navigation by detecting vessel orientation from onboard camera imagery, enabling early collision risk assessment in line with COLREGs regulations. A custom dataset with diverse ship types, environmental conditions, and viewing angles was constructed using publicly available sources and original photography. Eight orientation classes were labeled, and the dataset was split for training, validation, and testing. The lightweight YOLOv8n model was selected for its high inference speed and adaptability to limited hardware, making it suitable for deployment onboard vessels. Training was performed using Google Colab’s GPU environment, with progressive image resizing, parameter tuning, and various augmentation techniques to improve generalization. Evaluation metrics included mAP@0.5, mAP@0.5:0.95, precision, recall, and other relevant parameters. Despite promising trends, results indicated challenges in achieving high classification accuracy, with precision and class loss requiring further optimization. The study highlights the potential of real-time visual orientation detection for both civilian and defense maritime applications, while underlining the need for improved dataset balance and model tuning. SAVOS offers a foundation for future autonomous navigation systems and advanced vessel behavior monitoring.

Keywords: YOLO, computer vision, machine learning, aspect angle, mAP@0.5, mAP@0.5:0.95, precision, recall, SAVOS

[1] Kongsberg Gruppen, “AI-enabled next-generation vessel traffic management system in Singapore,” Kongsberg, May 2024. [Online]. Available: https://www.kongsberg.com/newsroom/stories/2024/5/ai-enabled-next-generation-vessel-traffic-management-system-in-singapore/ . [Accessed: 30 July 2025].
[2] Port of Hamburg, “Safe and secure tank farms thanks to digital twins,” Hafen Hamburg, [Online]. Available: https://www.hafen-hamburg.de/en/press/news/safe-and-secure-tank-farms-thanks-to-digital-twins/ . [Accessed: 30 July 2025].
[3] C. Rey, “Corpus Christi Port is using AI to track ships and train for emergencies,” Business Insider, May 2025. [Online]. Available: https://www.businessinsider.com/corpus-christi-port-ai-ship-tracking-emergency-training-2025-5 . [Accessed: 30 July 2025].
[4] Frontex, “PROMENADE: Artificial intelligence and big data for improved maritime awareness,” Frontex, [Online]. Available: https://www.frontex.europa.eu/innovation/eu-research/news-and-events/promenade-artificial-intelligence-and-big-data-for-improved-maritime-awareness-NoxagQ . [Accessed: 30 July 2025].
[5] O. D. Pipchenko, O. Burenkov, M. Tsymbal, and V. Pernykoza, “Identification of Weak Links in the ECDIS – Operator System Based on Simulator Training,” TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 15, no. 1, pp. 83–88, Mar. 2021, doi:10.12716/1001.15.01.07.
[6] J. R. Terven and D. M. Cordova-Esparaza, “A Comprehensive Review of YOLO: From YOLOv1 to YOLOv8 and Beyond,” arXiv preprint arXiv:2304.00501, Apr. 2023. [Online]. Available: https://arxiv.org/abs/2304.00501
[7] Stereolabs Inc., “Performance benchmark of YOLO v5, v7 and v8,” Stereolabs Blog, Jan. 12 2023. [Online]. Available: https://www.stereolabs.com/blog/performance-of-yolo-v5-v7-and-v8
[8] I. Lazarevich, M. Grimaldi, R. Kumar, S. Mitra, S. Khan, and S. Sah, “YOLOBench: Benchmarking Efficient Object Detectors on Embedded Systems,” arXiv preprint arXiv:2307.13901, Jul. 2023. [Online]. Available: https://arxiv.org/abs/2307.13901 . [Accessed: 30 July 2025].
[9] Z. He, K. Wang, T. Fang, L. Su, R. Chen, and X. Fei, “Comprehensive Performance Evaluation of YOLOv11, YOLOv10, YOLOv9, YOLOv8 and YOLOv5 on Object Detection of Power Equipment,” arXiv preprint arXiv:2411.18871, Nov. 2024. [Online]. Available: https://arxiv.org/abs/2411.18871 . [Accessed: 30 July 2025].
[10] Y. Li and S. Wang, “EGM-YOLOv8: A lightweight ship detection model with efficient feature fusion and attention mechanisms,” Journal of Marine Science and Engineering, vol. 13, no. 4, p. 757, Apr. 2025, doi: https://doi.org/10.3390/jmse13040757.
[11] J. Di, L. Sun, R. Zhang, and Q. Wu, “An enhanced YOLOv8 model for accurate detection of solid floating waste,” Scientific Reports, vol. 15, no. 1, p. 1632, Jan. 2025, doi: https://doi.org/10.1038/s41598-025-10163-2.
[12] P. Liu, “A high-accuracy YOLOv8-ResAttNet framework for maritime object recognition,” IET Image Processing, vol. 19, no. 3, pp. 145–157, Mar. 2025, doi: https://doi.org/10.1049/ipr2.70085.
[13] B. Zhao, H. Chen, X. Liu, and J. Huang, “Modular YOLOv8 optimization for real-time UAV maritime rescue object detection,” Scientific Reports, vol. 14, no. 1, p. 1158, Jan. 2024, doi: https://doi.org/10.1038/s41598-024-75807-1.
[14] X. Zhao and Y. Song, “Improved Ship Detection with YOLOv8 Enhanced with MobileViT and GSConv,” Electronics, vol. 12, no. 22, p. 4666, Nov. 2023, doi: https://doi.org/10.3390/electronics12224666.
[15] A. Haijoub, A. Hatim, A. Guerrero-Gonzalez, M. Arioua, and K. Chougdali, “Enhanced YOLOv8 ship detection empower unmanned surface vehicles for advanced maritime surveillance,” Journal of Imaging, vol. 10, no. 12, p. 303, Dec. 2024, doi: https://doi.org/10.3390/jimaging10120303.
[16] B. E. Ayesha, I. Ahmad, Z. Chen, and S. Ali, “Ship detection in remote sensing imagery for arbitrarily oriented object detection using YOLOv8 and U-Net,” arXiv preprint arXiv:2503.14534, Mar. 2025. [Online]. Available: https://arxiv.org/abs/2503.14534. [Accessed: 30 July 2025].
[17] Flickr. [Online]. Available: https://www.flickr.com/ [Accessed: Jul. 30, 2025].

The hull is a part of the vessel that is exposed to increased temperature and humidity changes during operation. One way to prevent the destruction of a ship’s hull is to create a superhydrophobic state on its surface. Basic models, namely the Wenzel and Cassie–Baxter models, accounting for the contact angle of water on solid surfaces relating to the influence of sur-face roughness on hydrophobicity are discussed. High efficiency of coating roughness is achieved through the use of nanomaterials that ensure super hydrophobicity of the surface. Drops of water do not wet such a surface, so at the slightest inclination towards the horizon, water rolls off it, capturing dust and dirt particles, leaving no traces of pollution. This surface state leads to a decrease in the resistance of the vessel’s movement; causes self-cleaning of portholes and the surface of the vessel from contamination; the possibility of cleaning the underwater part from fouling without dry dock; delays the formation of ice and in some cases fully prevents its formation.

Keywords: ship’s hull, superhydrophobic state, anti-icing, de-icing, nanotechnology

[1] Ph. Kumar, Principles of Nanotechnology, 2nd ed. Scitech Publications, 2020, 115 p.
[2] S. V. Kozytskyi and S. V. Kiriian, “Properties and behavior of nanoparticles,” Fizyka aerodyspersnyh system, no. 60, pp. 17–30, 2022, doi:10.18524/0367-1631.2022.60.265983.
[3] S. V. Kozytskyi, “Mikro- ta nanorozmirni krystaly sulfidy tzynku otrymani metodom vysokotemperaturnogo syntezu shcho samoposhuruetsia,” Fizyka aerodyspersnyh system, no. 61, pp. 32–42, 2023, doi:10.18524/0367-1631.2023.61.290948.
[4] S. V. Kozytskyi and S. V. Kiriian, “Vlastyvosti nanostrukturovanyh materialiv,” Sudnovi energetychni ustanovky. Naukovo-technichnyi zbirnyk, vol. 45, pp. 124–135, 2022, doi:10.31653/smf45.2022.123-135.
[5] S. V. Kozytskyi, “Zastosuvannia nanomaterialiv dlia zbilshennia nadiinosti ta resursu sudnovyh ustanovok,” Sudnovi energetychni ustanovky. Naukovo-technichnyi zbirnyk, vol. 48, pp. 31–45, 2024, doi:10.31653/smf48.2024.31-45.
[6] S. V. Kozytskyi, “Zastosuvannia nanomaterialiv dlia zapobigannia biologichnomu obrostanniy ta korozii korpusy sudna,” Sudnovodinnia. Zbirnyk naukovyh prats. NU “OMA”, no. 36, pp. 64–76, 2024, doi:10.31653/2306-5761.36.2024.64-76.
[7] X. Mao, X. Cui, and S. Chen, “Research progress of nanomaterial the prevention of biological fouling on ships,” J. Phys.: Conf. Ser., vol. 2002, Art. no. 012013, 2021, doi:10.1088/1742-6596/2002/1/012013.
[8] S. V. Kozytskyi and A. N. Zolotko, Moleculiapna phizyca. Pidruchnyc. Odesa: Astroprynt, 2011, 352 p.
[9] Y. Zheng, X. Gao, and L. Jiang, “Directional adhesion of superhydrophobic butterfly wings,” Soft Matter, vol. 3, pp. 178–182, 2007, doi:10.1039/b612667g.
[10] A. Safaee, D. K. Sarkar, and M. Farzaneh, “Superhydrophobic properties of silver-coated films on copper surface by galvanic exchange reaction,” Applied Surface Science, vol. 254, no. 8, pp. 2493–2498, 2008, doi:10.1016/j.apsusc.2007.09.073.
[11] D. K. Sarkar and M. Farzaneh, “Superhydrophobic coatings with reduced ice adhesion,” Journal of Adhesion Science and Technology, vol. 23, no. 9, pp. 1215–1237, 2009, doi:10.1163/156856109X433964.
[12] N. Li et al., “Micro/nano-cactus structured aluminium with superhydrophobicity and plasmon-enhanced photothermal trap for icephobicity,” Chemical Engineering Journal, vol. 429, Art. no. 132183, 2022, doi:10.1016/j.cej.2021.132183.
[13] A. Lafuma and D. Quere, “Superhydrophobic states,” Nature Materials, vol. 2, no. 7, pp. 457–460, 2003, doi:10.1038/nmat924.
[14] L. Feng, S. Li, Y. Li, et al., “Superhydrophobic surfaces: From natural to artificial,” Advanced Materials, vol. 14, no. 24, pp. 1857–1860, 2002, doi:10.1002/adma.200290020.
[15] Z. Youssef et al., “Dye-sensitized nanoparticles for heterogeneous photocatalysis: Case studies with TiO₂, ZnO, fullerene and graphene for water purification,” Dyes and Pigments, vol. 159, pp. 49–71, 2018, doi:10.1016/j.dyepig.2018.06.002.
[16] S. A. Higazy, M. S. Selim, A. M. Azzam, and S. A. El-Safty, “Hierarchical biocide-free silicone/graphene-silicon carbide nanocomposite coatings for marine antifouling and superhydrophobicity of ship hulls,” Chemical Engineering Science, vol. 291, Art. no. 119929, 2024, doi:10.1016/j.ces.2024.119929.
[17] S. V. Kozytskyi, “Pidvyshchennia efektyvnosti sudna chliahom vykorystannia nanomaterialiv dlia modernizatsii korpusu sudna,” Sudnovi energetychni ustanovky. Naukovo-technichnyi zbirnyk, vol. 49, pp. 131–143, 2024, doi:10.31653/smf340.2024.131-143.
[18] J. Li, E. Ueda, D. Paulssen, and P. A. Levkin, “Slippery lubricant-infused surfaces: Properties and emerging applications,” Advanced Functional Materials, vol. 29, no. 4, Art. no. 1802317, 2019, doi:10.1002/adfm.201802317.
[19] F. Wang et al., “Ice adhesion on different microstructure superhydrophobic aluminum surfaces,” Journal of Adhesion Science and Technology, vol. 27, no. 1, pp. 58–67, 2012, doi:10.1080/01694243.2012.701506.
[20] Brush-Kart, “Official website,” [Online]. Available: https://www.brush-kart.com/eng. [Accessed: Sep. 10, 2025].
[21] Demetra-5, “Catalog,” [Online]. Available: http://www.demetra5.kiev.ua/ua/catalog/seaey. [Accessed: Sep. 10, 2025].
[22] M. Mao et al., “Scalable robust photothermal superhydrophobic coatings for efficient anti-icing and de-icing in simulated/real environments,” Nature Communications, vol. 15, Art. no. 9610, 2024, doi:10.1038/s41467-024-54058-8.
[23] S. Chang, H. Qi, S. Zhou, and Y. Yang, “Experimental and numerical study on freezing process of water droplets under surfaces with different wettability,” Applied Thermal Engineering, vol. 219, Part B, Art. no. 119516, 2023, doi:10.1016/j.applthermaleng.2022.119516.
[24] Y. Li et al., “Solar deicing nanocoatings adaptive to overhead powerlines,” Advanced Functional Materials, vol. 32, no. 25, Art. no. 2113297, 2022, doi:10.1002/adfm.202113297.
[25] T. Wang, Y. Zheng, A.-R. O. Raji, Y. Li, W. K. A. Sikkema, and J. M. Tour, “Passive anti-icing and active deicing films,” ACS Applied Materials & Interfaces, vol. 8, no. 22, pp. 14169–14173, 2016, doi:10.1021/acsami.6b03060.
[26] Y. Liu et al., “Robust photothermal coating strategy for efficient ice removal,” ACS Applied Materials & Interfaces, vol. 12, no. 41, pp. 46981–46990, 2020, doi:10.1021/acsami.0c13367.
[27] D. Li, L. Ma, B. Zhang, and S. Chen, “Facile fabrication of robust and photo-thermal super-hydrophobic coating with efficient ice removal and long-term corrosion protection,” Chemical Engineering Journal, vol. 450, Part 4, Art. no. 138429, 2022, doi:10.1016/j.cej.2022.138429.
[28] J. Wei, S. Yang, X. Xiao, and J. Wang, “Hydrophobic solid photothermal slippery surfaces with rapid self-repairing, dual anti-icing/deicing, and excellent stability based on paraffin and etching,” Langmuir, vol. 40, no. 14, pp. 7747–7759, 2024, doi:10.1021/acs.langmuir.4c00440.

The vessel domain of danger is a widely used construct in collision-avoidance research, yet definitions vary in methods, shapes, safety criteria, influencing factors, and interpretation. Prior studies have used circular, elliptical, polygonal, composite, and (a)symmetric domains, placed around targets, own ship, or both. This paper proposes two target-centred danger domains tailored for constricted waters. The first comprises two half-circles bridged by a rectangular insert; the second combines a half-ellipse, a half-circle, and a rectangular insert. These shapes are argued to be rational for close-quarters encounters. Domains are parameterized by target size, the speed ratio (target/own ship), and user-selected safe passing limits abeam and astern, with inputs sourced from radar and AIS. To include own-ship dimensions, a corrective expansion is applied based on own-ship length, beam, and the difference between true course and course relative to the target. Algorithms are developed to compute quantities needed for risk assessment and maneuver selection, notably the boundaries of dangerous courses and speeds of the own ship relative to a given target. Procedures are provided both neglecting and accounting for own-ship inertia. Worked examples demonstrate the algorithms’ validity and illustrate practical use in identifying prohibited headings/speeds and determining feasible evasive actions under confined-water constraints. The approach offers a structured, sensor-driven framework for collision-risk quantification and maneuver planning that adapts to target characteristics, encounter geometry, hydrodynamic limitations, and operator-defined safety margins.

Keywords: collision avoidance, domain of danger, risk of collision, encounter situation, evading maneuver

[1] Baran A., Fiskin R., Kişi H. A Research on Concept of Ship Safety Domain. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 12, No. 1, 2018. pp. 43-47. https://doi:10.12716/1001.12.01.04.
[2] Dinh G. H., Im N. K., The combination of analytical and statistical method to define polygonal ship domain and reflect human experiences in estimating dangerous area, International Journal of e-Navigation and Maritime Economy, vol. 4, 2016. pp. 97-108, https://doi.org/10.1016/j.enavi.2016.06.009
[3] Fışkın R, Nasibov E., Yardımcı M.O. Polygonal Type Fuzzy Ship Domain-Based Decision Support System for Collision Avoidance Route Planning. Journal of ETA Maritime Science. 11 (1). 2023. pp. 2-13. https://doi: 10.4274/jems.2023.23245.
[4] Fukuto J, Imazu H. New collision alarm algorithm using obstacle zone by target (OZT). 9th IFAC Conference on Control Applications in Marine Systems. The International Federation of Automatic Control, Osaka, Japan. 2013. pp. 91-96. https://doi.org/10.3182/20130918-4-JP-3022.00044.
[5] Liu, Z.; Wu, Z.; Zheng, Z.; Yu, X.; Bu, X.; Zhang, W. A Domain-Based Model for Identifying Regional Collision Risk and Depicting Its Geographical Distribution. J. Mar. Sci. Eng. 2023, pp.11, https://doi.org/10.3390/ jmse11112092.
[6] Liu J., Feng Z., Li Z., Wang M., Wen L. R., Dynamic Ship Domain Models for Capacity Analysis of Restricted Water Channels, Journal of Navigation, vol. 69, 2016. pp. 481-503. https://doi:10.1017/S0373463315000764
[7] Marcjan K, Gucma L, Kotkowska D. The Collision Risk Management Method for Ships Navigating on Coastal Waters Based on Ship Domain and Near-Miss Concept. European Research Studies Journal Volume XXIV, Issue 4, 2021. pp. 127-146. https://doi:10.35808/ersj/2567.
[8] Pietrzykowski Z, Wielgosz M. Effective ship domain – Impact of ship size and speed. Ocean Engineering. Volume 219, 2021, pp.1-20. https://doi.org/10.1016/j.oceaneng.2020.108423.
[9] Rawson A, Rogers E, Foster D, Phillips D Practical Application of Domain Analysis: Port of London Case Study, Journal of Navigation, vol. 67, 2014. pp. 193-209. https://doi:10.1017/S0373463313000684.
[10] Sawada R, Sato K, Majima T. Automatic ship collision avoidance using deep reinforcement learning with LSTM in continuous action spaces. Journal of Marine Science and Technology, 26(1). 2021. pp. 509-524. https://doi.org/10.1007/s00773-020-00755-0
[11] Szlapczynski R., Szlapczynska J., Review of ship safety domains: Models and applications, Ocean Engineering, vol. 145, 2017. pp. 277-289. https://doi:10.1016/j.oceaneng.2017.09.020
[12] Szlapczynski R, Szlapczynska J. A ship domain-based model of collision risk for near-miss detection and Collision Alert Systems. Reliability Engineering & System Safety. Volume 214, 2021. https://doi.org/10.1016/j.ress.2021.107766.
[13] Tianyu Yang, Xin Wang and Zhengjiang Liu. A Novel Ship Domain-oriented Parameter of Ship Collision Risk Considering the Ship Maneuverability and Encounter Situation. Journal of Marine Science and Application. 22. 2023. pp. 181-198. https://doi.org/10.1007/s11804-023-00330-0
[14] Wang Y, Chin H-C. An Empirically-Calibrated Ship Domain as a Safety Criterion for Navigation in Confined Waters. Journal of Navigation. 69(2). 2016, pp. 257-276. https://doi:10.1017/S0373463315000533.
[15] Wielgosz M.. Ship Domain in Open Sea Areas and Restricted Waters: an Analysis of Influence of the Available Maneuvering Area. Transnav. Volume 11. Number 1. March 2017. pp. 99-104. https://doi: 10.12716/1001.11.01.11.
[16] Zhai P., Zhang Y., Shaobo W. Intelligent Ship Collision Avoidance Algorithm Based on DDQN with Prioritized Experience Replay under COLREGs. J. Mar. Sci. Eng. 10, 585. 2022. pp. 1-29. https://doi.org/10.3390/jmse10050585.

The article summarizes an assessment of the readiness of Ukraine’s hydrographic infrastructure to transition from IHO S-57 to the next-generation S-100 and IALA S-200 standards. It shows that these standards provide a unified model for maritime geospatial data, support for multidimensional layers (bathymetry, currents, weather), compatibility with GIS, and secure exchange via SECOM, which is a critical prerequisite for integration into the global e-navigation system. The study finds partial readiness: the cartographic base and human capital are the most developed, whereas data-exchange systems and the regulatory framework require substantial updates. In this context, the article proposes considering a concept for implementing maritime information architecture with a unified data repository and product catalogues (S-128); services for disseminating charts (S-101), bathymetry (S-102), navigational warnings (S-124), and aids-to-navigation data (S-201); as well as SECOM-based interoperability. The implementation priorities outlined include modernization of shore-based systems, deployment of a national marine geospatial data infrastructure, S-100/S-200 web services, a transition roadmap, S-124/S-201 prototypes, staff training, and formal recognition of S-100 products in national regulation. Comprehensive implementation will enhance navigational safety, the timeliness of information, and the environmental sustainability of Ukraine’s maritime activities.

Keywords: aids to navigation, navigation standards, object catalogue, information technology, hydrographic data model, digital information service

[1] International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), Guideline G1106 Ed.2.1: Producing an IALA S-200 Series Product Specification, Jun. 2017.
[2] International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), Guideline G1087: Procedures for the Management of the IALA Domains under the IHO GI Register.
[3] International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), Recommendation R1019: Provision of Maritime Services in the Context of e-Navigation in the Domain of IALA.
[4] International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), Guideline G1128: Specification of e-Navigation Technical Services, 2024.
[5] International Hydrographic Organization (IHO), “IALA activities affecting HSSC – IALA Presentation,” Jun. 2023. [Online]. Available: https://iho.int/uploads/user/ Services%20and%20Standards/HSSC/HSSC15/HSSC15_2023_07.3A_EN_IALA_report.pdf
[6] International Electrotechnical Commission (IEC), IEC 63173-2 Ed.1: Maritime Navigation and Radiocommunication Equipment and Systems—Data Interface—Part 2: Secure Exchange and Communication of S-100 Based Products (SECOM).
[7] International Hydrographic Organization (IHO), S-100 Universal Hydrographic Data Model, ver. 2.0.0, Jun. 2015. [Online]. Available: https://iho.int/en/introduction-0
[8] International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA), “G1106: Producing an IALA S-200 Series Product Specification,” Ed. 3.0, revised Jun. 13, 2025. [Online]. Available: https://www.iala.int/product/g1106/
[9] International Maritime Organization (IMO), MSC.467(101): Guidance on the Definition and Harmonization of the Format and Structure of Maritime Services in the Context of e-Navigation.
[10] International Maritime Organization (IMO), MSC.1/Circ.1610: Initial Descriptions of Maritime Services in the Context of e-Navigation.
[11] International Organization for Standardization (ISO), “Geographic information – Conceptual schema language,” ISO 19103:2024, 2024. [Online]. Available: iso.org/standard/83454.html.
[12] ISO, “Geographic information — Procedures for item registration – Part 1: Fundamentals,” ISO 19135-1:2015 (with Amd 1:2021), 2015/2021. [Online]. Available: iso.org/standard/54721.html; Amd 1: iso.org/standard/78896.html.
[13] ISO, “Geographic information – Feature concept dictionaries and registers,” ISO 19126:2021, 2021. [Online]. Available: iso.org/standard/78898.html.
[14] ISO, “Geographic information – Rules for application schema (General Feature Model),” ISO 19109:2025 (3rd ed.), 2025. [Online]. Available: iso.org/standard/84700.html.
[15] ISO, “Geographic information – Metadata – Part 1: Fundamentals,” ISO 19115-1:2014 (with Amd 1:2018, Amd 2:2020), 2014/2018/2020. [Online]. Available: iso.org/standard/53798.html; Amd 1: iso.org/standard/73118.html; Amd 2: iso.org/standard/80275.html.
[16] ISO, “Geographic information — Metadata — Part 2: Extensions for acquisition and processing,” ISO 19115-2:2019, 2019. [Online]. Available: iso.org/standard/67039.html.
[17] ISO, “Geographic information — Metadata — Part 3: XML schema implementation for fundamental concepts,” ISO 19115-3:2023, 2023. [Online]. Available: iso.org/standard/80874.html.
[18] ISO, “Geographic information — Data quality — Part 1: General requirements,” ISO 19157-1:2023, 2023. [Online]. Available: iso.org/standard/78900.html.
[19] ISO, “Geographic information — Data quality — Part 2: XML schema implementation,” ISO/TS 19157-2:2016, 2016. [Online]. Available: iso.org/standard/66197.html.
[20] ISO, “Geographic information — Methodology for feature cataloguing,” ISO 19110:2016, 2016. [Online]. Available: iso.org/standard/57303.html.
[21] ISO, “Geographic information — Referencing by coordinates,” ISO 19111:2019 (with Amd 1:2021, Amd 2:2023), 2019/2021/2023. [Online]. Available: iso.org/standard/74039.html; Amd 1: iso.org/standard/81673.html; Amd 2: iso.org/standard/86173.html.
[22] ISO, “Geographic information — Spatial schema,” ISO 19107:2019, 2019. [Online]. Available: iso.org/standard/66175.html.
[23] ISO, “Geographic information — Schema for coverage geometry and functions — Part 1: Fundamentals,” ISO 19123-1:2023, 2023. [Online]. Available: iso.org/standard/70743.html.
[24] ISO, “Geographic information — Imagery, gridded and coverage data framework,” ISO/TS 19129:2009, 2009 (current TS). [Online]. Available: iso.org/standard/43041.html.
[25] ISO, “Geographic information — Data product specifications,” ISO 19131:2022 (2nd ed.), 2022. [Online]. Available: iso.org/standard/85092.html.
[26] International Hydrographic Organization (IHO), “Standards for Hydrographic Surveys,” IHO S-44, Ed. 6.2.0, Oct. 2024. [Online]. Available: https://iho.int/uploads/user/pubs/standards/s-44/S-44_Edition_6.2.0_adopted.pdf
[27] International Hydrographic Organization (IHO), S-99 Operational Procedures, ver. 1.1.0, Nov. 2012.

This paper presents a method for determining the effective observed coordinates of a ship using bearings and distances to several landmarks, accounting for redundant measurements and assuming normally distributed errors. Accurate and continuous monitoring of a vessel’s position is essential to prevent navigational accidents. Modern Electronic Chart Display and Information Systems (ECDIS) allow the determination of a ship’s location from measured bearings and distances to charted landmarks. Since these measurement errors follow a normal distribution, the maximum likelihood approach coincides with the least squares method. Each measurement is expressed as a line of position (LOP) equation, for which the transfer magnitudes and gradient directions are derived from the measured values. Analytical expressions are obtained for the probability density functions of LOP errors, leading to a system of normal equations whose coefficients depend on the derived parameters. Solving these equations yields statistically optimal estimates of the vessel’s coordinates. The results confirm the applicability of the proposed method for improving the positional accuracy of ECDIS and enhancing navigational safety in real-time operations.

Keywords: navigational safety, efficiency of the coordinates, lines of position, normal equations, excessive measurements

[1] Džunda M., Čikovský S. and Melniková L. “Model of the Signal of the Galileo Satellite Navigation System”, TransNav, International journal on marine navigation and safety of sea transportation, vol. 17, no. 1, doi: 10.12716/1001.17.01.04, pp. 51-59, 2023.
[2] Malić E., Sikirica N., Špoljar D. and Filjar R. “A Method and a Model for Risk Assessment of GNSS Utilisation with a Proof-of-Principle Demonstration for Polar GNSS Maritime Applications”, TransNav, International journal on marine navigation and safety of sea transportation, vol. 17, no. 1, doi:10.12716/1001.17.01.03, pp. 43-50, 2023.
[3] Džunda M. “Model of the Motion of a Navigation Object in a Geocentric Coordinate System”, TransNav, International journal on marine navigation and safety of sea transportation, vol. 15, no. 4, doi:10.12716/1001.15.04.10, pp. 791-794, 2021.
[4] Pavić I., Mišković J., Kasum J. and Alujević D. “Analysis of Crowdsourced Bathymetry Concept and It’s Potential Implications on Safety of Navigation”, TransNav, International journal on marine navigation and safety of sea transportation, vol. 14, no. 3, doi:10.12716/1001.14.03.21, pp. 681-686, 2020.
[5] Džunda M., Čikovský S. and Melniková L. “Model of the Random Phase of Signal E6 of the Galileo Satellite Navigation System”, TransNav, International journal on marine navigation and safety of sea transportation, vol. 17, no. 1, doi:10.12716/1001.17.01.05, pp. 61-68, 2023.
[6] W. Filipowicz. “Position Fixing and Uncertainty”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 17, no. 4, doi:10.12716/1001.17.04.15, pp. 887-893, 2023.
[7] D. A. Hsu, “An analysis of error distribution in navigation”, The Journal of Navigation, Vol. 32, no. 3. pp. 426 – 429, 2003.
[8] V.T. Kondrashikhin Location of ship. Transport, 1989.
[9] I. Vorokhobin, O. Haichenia, V. Sikirin and I. Fusar, “Application of Orthogonal Decomposition of Mixed Laws’ Density Distribution of Navigational Measurement Errors”, In the 25th International Scientific Conference Transport Means 2021 Sustainability: Research and Solutions, 06.10, 2021, pp. 477-481.
[10] Luis Monteiro, “What is the accuracy of DGPS?”, J. Navig. vol. 58, no. 2, pp. 207-225, 2005.
[11] V.E. Sikirin, “Description of navigation errors by the generalized distributing of Puasson”, Sudnovonnya, Vyp. 26. – pp. 152 – 156, 2016.
[12] D.V. Astayrin., V.E. Sikirin, I.I. Vorokhobin and B.M. Alekseychuk, Estimation of exactness of coordinates of ship at the surplus measuring. Saarbrucken, Deutschland: LAP LAMBERT Academic Publishing, 2017.
[13] I. Vorokhobin, O. Haichenia, V. Sikirin and V. Severin, “Determination of the Law of Probability Distribution of Navigation Measurements”, In the 24th International Scientific Conference Transport Means 2020 Sustainability: Research and Solutions, 30.09,2020, pp. 707-711.
[14] D. Astaykin, A. Golikov, A. Bondarenko, O. Bulgakov, “The Effectiveness of Ship’s Position Using the Laws of Distribution of Errors in Navigation Measurements”, In the 24th International Scientific Conference Transport Means 2020 Sustainability: Research and Solutions, 30.09,2020, pp. 662-666.
[15] I.O. Burmka, B.M. Alekseychuk “Accuracy of the coordinates of the ship’s designated place, calculated by the least squares method, in the times of overworldly worlds” Sudnovodinya, Vyp. 35, DOI: 10.31653/2306-5761.35.2023.10-21, pp. 10-21, 2023.
[16] B.M. Aliyeksiyeychuk, “Dependence of observation accuracy on significant factors and ways to improve it”, Sudnovodinnya, Vyp.36, DOI: 10.31653/2306-5761.36.2024.10-19, pp. 10-19, 2024.
[17] V.M. Mudrov, V.L. Kushko. Methods of treatment of measurings, 1976.
[18] V.V. Stepanenko. “Efficiency of assessing the parameters of the situation of dangerous approach of ships”, Sudnovodinnya, Vyp. 2, pp. 201 – 209, 2000.
[19] R. Bober, P. Grodzicki, Z. Kozlowski and A.Wolski, “The DGPS system improve safety of navigation within the port of Szczecin”, In the 12 Saint Petersburg International Conference on Integrated Navigation Systems, 23.05, 2005, pp. 192-194.
[20] Kubo Masayoshi, Sakakibara Shigeki, Hasegawa Yoshimi and Nagaoka Tadao.”Research of method of calculation of probability of collision of ship with the rectangular bull of bridge at tearing down by wind and flow”, Jap. Inst. Navig. no. 104, pp. 225-233, 2001.

The article presents the results of the development and verification of a system of quantitatively measurable criteria for assessing practical ship-handling skills, aimed at increasing the objectivity of maritime training evaluation. The proposed approach bridges the gap between the qualitative requirements of the STCW Code and the actual performance parameters of maneuvers that determine navigational safety. Based on expert consultations, analysis of international standards (STCW, PIANC, EAU), and hydrodynamic studies, a set of ten training exercises was developed to cover typical maneuvering scenarios in confined waters. For each exercise, a system of performance criteria was defined, including speed limits, acceptable approach angles, and temporal and spatial trajectory deviations. The verification of the proposed criteria was carried out using simulation modeling, confirming the adequacy and applicability of the selected parameters. The developed indicators were integrated into a Learning Management System (LMS), providing automated performance assessment, data synchronization, and objective feedback throughout the training process. The methodology demonstrated practical efficiency and adaptability across various training formats — including full-mission, individual, and virtual-reality simulators. Its implementation promotes the standardization of assessment procedures, enhances transparency and reliability of training results, and establishes a foundation for developing automated certification systems in maritime education.

Keywords: ship handling, safety of navigation, simulators, maritime education and training, containerships, Learning Management System, e-learning, skill evaluation criteria

[1] O. Pipchenko and N. Konon, “Met Enhancement Using Modern Simulation Technologies: Xr, Web andFull Mission,” Journal of Maritime Research, Vol XXII. No. I (2025) pp 404–412. [Online]. Available: https://www.jmr.unican.es/jmr/article/view/962/1001. [Accessed Aug. 11, 2025].
[2] O. Pipchenko, N. Konon, V. Konon, O. Fomin and O. Kozyr, “Design and validation of prac-tical criteria for assessing ship handling competence”, in The 3rd SEA the Future 2025, Feb-ruary 26-28, 2025, Pattaya, Thailand.
[3] International Convention on Standards of Training, Certification and Watchkeeping for Sea-farers (STCW), including 2010 Manila Amendments, International Maritime Organization, London, UK, 2017.
[4] IMO Model Course 1.22: Ship Simulator and Bridge Teamwork, International Maritime Or-ganization, London, UK, 2012.
[5] IMO Model Course 7.01: Master and Chief Mate and IMO Model Course 7.03: Officer in Charge of a Navigational Watch, International Maritime Organization, London, UK, 2014.
[6] IMO Resolution A.960(23): Recommendations on Training and Certification and Operation-al Procedures for Maritime Pilots Other than Deep-Sea Pilots, International Maritime Organ-ization, London, UK, Dec. 2003.
[7] International Convention on Standards of Training, Certification and Watchkeeping for Sea-farers (STCW), including the 2010 Manila Amendments, Table A-II/1, “Specification of minimum standard of competence for officers in charge of a navigational watch on ships of 500 gross tonnage or more,” International Maritime Organization, London, UK, 2017.
[8] International Convention on Standards of Training, Certification and Watchkeeping for Sea-farers (STCW), including 2010 Manila Amendments, Table A-II/2, “Specification of mini-mum standard of competence for masters and chief mates on ships of 500 gross tonnage or more,” International Maritime Organization, London, UK, 2017.
[9] Y. Kunieda, K. Kumagai, H. Kashima and K. Murai, “An Effective Training and Evaluation Method for Anchoring Training in Maritime Education,” World Journal of Social Science Research, vol. 7, no. 2, pp. 12–23, May 2020, doi: 10.22158/wjssr.v7n2p12 .
[10] J. Ernstsen and S. Nazir, “Performance assessment in full-scale simulators – A case of mari-time pilotage operations,” Safety Science, vol. 129, p. 104775, 2020, doi: 10.1016/j.ssci.2020.104775.
[11] H. M. Tusher, S. Nazir, S. Ghosh, and R. Rusli, “Seeking the Best Practices of Assessment in Maritime Simulator Training: A Systematic Review,” TransNav – Int. J. Marine Navigation and Safety of Sea Transportation, vol. 17, no. 1, pp. 105–114, 2023, doi: 10.12716/1001.17.01.10.
[12] O. Atik and O. Arslan, “Use of Eye Tracking for Assessment of Electronic Navigation Com-petency in Maritime Training,” Journal of Eye Movement Research, vol. 12, no. 3, p. 2, 2019, doi: 10.16910/jemr.12.3.2.
[13] S. Bhagat and Z. H. Munim, “Application of Image Recognition in Nautical Simulator Train-ing Assessment,” in Lecture Notes in Networks and Systems, vol. 1274, MIS4TEL 2024, pp. 61–70, Springer, Cham, 2025, doi: 10.1007/978-3-031-84170-5.
[14] Z. H. Munim and T.-E. Kim, “Towards Automated Performance Assessment for Maritime Navigation Training Using Simulator and Learning Analytics,” WMU Journal of Maritime Affairs, vol. 23, pp. 1–20, 2025, doi: 10.12716/1001.11.02.03.
[15] Roubos, Alfred & Groenewegen, Leon & Peters, Dirk Jan, “Berthing velocity of large seago-ing vessels in the port of Rotterdam,” Marine Structures, 51, pp. 202-219, 2017, doi: 10.1016/j.marstruc.2016.10.011.
[16] Recommendations of the Committee for Waterfront Structures, Harbours and Waterways: EAU 2015, 9th English edition (translation of the 11th German edition), Hamburg/Essen: Hafenbautechnische Gesellschaft e. V. (HTG) and Deutsche Gesellschaft für Geotechnik e. V. (DGGT), Ernst & Sohn/Wiley-VCH, 2015, 650 p.
[17] International Navigation Association (PIANC), “Guidelines for the Design of Fender Sys-tems: 2002, Report of Working Group 33 of the Maritime Navigation Commission,” Brus-sels, Belgium: PIANC, 2002.
[18] Yasukawa, H., Yoshimura, Y., “Introduction of MMG Standard Method for Ship Maneuver-ing Predictions,” Journal of Marine Science and Technology, Vol. 20, pp. 37–52, 2015, doi: 10.1007/s00773-014-0293-y.
[19] Y. Yoshimura and Y. Masumoto, “Hydrodynamic database and manoeuvring prediction method with medium high-speed merchant ships and fishing vessels,” in Proc. Int. Conf. Ma-rine Simulation and Ship Manoeuvrability (MARSIM 2012), Singapore, Apr. 2012, pp. 494-503.
[20] Y. Yoshimura et al., “The Maneuvering Committee. Final Report and Recommendations to the 24th ITTC,” in Proc. 24th Int. Towing Tank Conf. (ITTC), Oct. 2005, Volume I, doi: 10.1632/074069505X82824.
[21] O. D. Pipchenko, M. Tsymbal, and V. Shevchenko, “Features of an Ultra-large Container Ship Mathematical Model Adjustment Based on the Results of Sea Trials,” TransNav, Int. J. Marine Navigation and Safety of Sea Transportation, vol. 14, no. 1, pp. 163–170, 2020, doi: 10.12716/1001.14.01.20.
[22] H.-Y. Lee and S.-S. Shin, “The prediction of ship’s manoeuvring performance in initial de-sign stage,” in Practical Design of Ships and Mobile Units, Elsevier, 1998, pp. 633–639, doi: 10.1016/S0928-2009(98)80205-9.
[23] O. Pipchenko, N. Konon and Ye. Bogachenko. “Mathematical modelling of “ASD tug – ma-rine vessel” interaction considering tug’s maneuverability and stability limitations,” Journal of Maritime Research, vol. 20, no. 2, pp.117–124, August 2023, DOI: 10.5281/zenodo.8370780.

The article addresses the problem of increasing the accuracy of measuring navigational parameters, in particular the angular coordinates, of the ship’s radar (RADAR) under complex pilotage conditions. A method based on adaptive control of the polarization parameters of the probing and received signals is proposed. The relationship between the classical radar equation and modern polarimetric methods is established. It is shown that representing the interaction of a radio wave with a navigational target through the Mueller matrix, expressed via the Stokes parameters, makes it possible to optimize the signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR). The Mueller matrix is interpreted as an energy scattering matrix that describes the transformation of the wave’s power characteristics. It is substantiated that the deliberate selection of the polarization of the transmitting and receiving antennas, based on the analysis of the full polarization signature of the target, can significantly improve the accuracy of determining its azimuth, which is critically important for ensuring navigation safety in confined waters. Additionally, the synergistic effect of integrating a polarimetric radar with high-precision Portable Pilot Units (PPU), which provide reference kinematic parameters of the vessel necessary for more efficient target discrimination and polarization parameter adaptation, is investigated.

Keywords: pilotage, ship radar, radio wave polarization, Stokes parameters, Mueller matrix, radar equation, angular measurement accuracy, adaptive polarization, Portable Pilot Unit, PPU, SafePilot

[1] Skolnik M., Radar Handbook, 3rd ed. McGraw-Hill, 2008.
[2] Aubry A., De Maio A., and Farina A., Polarimetric Radar Signal Processing. Scitech Publishing (IET Radar, Sonar & Navig.), New York, 2023, doi: 10.1049/SBRA549E
[3] Boerner W. M., “Polarimetric scattering and SAR polarimetry,” IEEE Trans. Geosci. Remote Sens., 2003.
[4] Ulaby F. T. and Elachi C., Eds., Radar Polarimetry for Geoscience Applications. Artech House, 1990.
[5] Mott H., Antennas for Radar and Communications: A Polarimetric Approach. John Wiley & Sons, 2007.
[6] Boerner W. M., Mott H., Luneburg E., et al., “Polarimetry in radar technology,” in Handbook of Radar Measurement. Artech House, 1998.
[7] Collin B., Polarimetric Radar Signal Processing. Wiley, 2013.
[8] Krogager E., “Polarimetric radar target decomposition,” IEE Proc., 1992.
[9] Zhang S., Wang T., Liu C., and Wang D., “A space–time adaptive processing method based on sparse Bayesian learning for maneuvering airborne radar,” Sensors, vol. 22, no. 15, art. no. 5479, 2022, doi: 10.3390/s22155479
[10] Dingle-Robertson L., McNairn H., Jiao X., McNairn C., and Ihuoma S., “Monitoring crops using compact polarimetry and the RADARSAT Constellation Mission,” Can. J. Remote Sens., vol. 48, no. 6, pp. 1–21, 2022, doi: 10.1080/07038992.2022.2121271
[11] Wang H., Zhou Z., Turnbull J., Song Q., and Qi F., “Three-component decomposition based on Stokes vector for compact polarimetric SAR,” Sensors, vol. 15, no. 9, pp. 24087–24114, 2015, doi: 10.3390/s150924087
[12] Badanis K. E., “Automated monitoring of road surfaces taking into account the correction of tropospheric delays of satellite navigation signals,” Vestn. Samarsk. Gos. Tekhn. Univ. (Tekhn. nauk), vol. 33, no. 1, pp. 7–20, 2025, doi: 10.14498/tech.2025.1.1
[13] Trelleborg Marine and Infrastructure, SafePilot CAT ROT & CAT I Portable Piloting Units [Brochure], 2024. [Online]. Available: https://www.trelleborg.com/marine-and-infrastructure/-/media/marine-systems/resources/brochures/downloads/safepilot-cat-rot.pdf. [Accessed: Sept. 23, 2025].
[14] Trelleborg Marine and Infrastructure, SafePilot Pro User Guide [User Manual], 2023.
[15] Mikkelsen T., “Trelleborg PPU (HAS, SBAS),” presentation at User Consultation Platform, EUSPA, 2022. [Online]. Available: https://www.euspa.europa.eu/sites/default/files/12._space_week_trelleborg.pdf [Accessed: Sep. 23, 2025].
[16] The International Taskforce on Port Call Optimization (ITPCO), A Practical Guide to Portable Pilot Units (PPU). The Nautical Institute, 2019.
[17] Trelleborg Marine and Infrastructure, SafePilot SmartPort System [Brochure]. [Online]. Available: https://www.trelleborg.cn/marine-and-infrastructure/-/media/marine-and-infrastructure/resources/brochures/downloads/safepilot-port-system.pdf [Accessed: Sep. 23, 2025].
[18] Rawson C. and Patterson L., “Enhancing pilotage with high-accuracy portable navigation systems,” in Proc. Int. Assoc. Maritime Univ. (IAMU) Conf., 2021, pp. 112–120.

This study examines environmental protection during sea passages in the coastal waters of Northern Europe, focusing on nitrogen oxides (NOx) from marine diesel exhaust as a primary source of uncontrolled air pollution, especially hazardous in high-humidity regions. In response, MARPOL designates special emission control areas that impose stricter NOx limits. We evaluate exhaust gas recirculation (EGR) as a principal, widely used measure to meet these limits during operations within such areas. Experiments were conducted on a 65,000-DWT general cargo vessel trading in Northern European special areas. The ship was fitted with a combined EGR arrangement incorporating both high- and low-pressure loops. We propose assessing EGR effectiveness—and, by extension, the environmental friendliness of passages—in terms of an environmental sustainability index referenced to NOx emissions. Results show that the integrated EGR system enabled the vessel to meet MARPOL NOx requirements across test conditions. The most effective operating modes corresponded to the highest practicable recirculation rates of both loops. Under these conditions, the environmental sustainability index reached 30.00–35.88%, representing the maximum measured reduction potential within the study. These findings support complex EGR control as a viable pathway for compliant, lower-impact operations in Northern European coastal waters.

Keywords: coastal waters, environmental indicators, exhaust gas recirculation system, navigational passage, nitrogen oxide emissions, maritime transport, special ecological areas

[1] Maryanov, D., “Reduced energy losses during transportation of drilling fluid by platform supply vessels,” Technology Audit and Production Reserves, vol. 2, no. 1(64), pp. 42–50, 2022, doi: 10.15587/2706-5448.2022.256473.
[2] Madey, V., “Assessment of the efficiency of biofuel use in the operation of marine diesel engines,” Technology Audit and Production Reserves, vol. 2, no. 1(64), pp. 34–41, 2022, doi: 10.15587/2706-5448.2022.255959.
[3] Khlopenko, M., I. Gritsuk, O. Sharko, and E. Appazov, “Increasing the accuracy of the vessel’s course orientation,” Technology Audit and Production Reserves, vol. 1, no. 2(75), pp. 25–30, 2024, doi: 10.15587/2706-5448.2024.298518.
[4] Wang, Z., Q. Ma, Z. Zhang, Z. Li, C. Qin, J. Chen, and C. Peng, “A study on monitoring and supervision of ship nitrogen-oxide emissions and fuel-sulfur-content compliance,” Atmosphere, vol. 14, p. 175, 2023, doi: 10.3390/atmos14010175.
[5] Kong, K.-J., and S.-C. Hwang, “Development and performance evaluation experiment of a device for simultaneous reduction of SOx and PM,” Energies, vol. 17, p. 3337, 2024, doi: 10.3390/en17133337.
[6] Golovan, A., I. Gritsuk, and I. Honcharuk, “Reliable ship emergency power source: A Monte Carlo simulation approach to optimize remaining capacity measurement frequency for lead-acid battery maintenance,” SAE International Journal of Electrified Vehicles, vol. 13, no. 2, pp. 179–189, 2024, doi: 10.4271/14-13-02-0009.
[7] Melnyk, O., S. Onyshchenko, and O. Onishchenko, “Development measures to enhance the ecological safety of ships and reduce operational pollution to the environment,” Scientific Journal of Silesian University of Technology. Series Transport, vol. 118, pp. 195–206, 2023, doi: 10.20858/sjsutst.2023.118.13.
[8] Wang, W., G. Wang, Z. Wang, J. Lei, J. Huang, X. Nie, and L. Shen, “Optimization of Miller cycle, EGR, and VNT on performance and NOx emission of a diesel engine for range extender at high altitude,” Energies, vol. 15, p. 8817, 2022, doi: 10.3390/en15238817.
[9] Petrychenko, O., and M. Levinskyi, “Trends and preconditions for widespread adoption of liquefied natural gas in maritime transport,” Transport Systems and Technologies, vol. 43, pp. 21–36, 2024, doi: 10.32703/2617-9059-2024-43-2.
[10] Petrychenko, O., M. Levinskyi, D. Prytula, and A. Vynohradova, “Fuel options for the future: A comparative overview of properties and prospects,” Transport Systems and Technologies, vol. 41, pp. 96–106, 2023, doi: 10.32703/2617-9059-2023-41-8.
[11] Sagin, S. V., and O. A. Kuropyatnyk, “Using exhaust gas bypass for achieving the environmental performance of marine diesel engines,” Austrian Journal of Technical and Natural Sciences, nos. 7–8, pp. 36–43, 2021, doi: 10.29013/AJT-21-7.8-36-43.
[12] Sagin, S., and A. Sagin, “Development of method for managing risk factors for emergency situations when using low-sulfur content fuel in marine diesel engines,” Technology Audit and Production Reserves, vol. 5, no. 1(73), pp. 37–43, 2023, doi: 10.15587/2706-5448.2023.290198.
[13] Fischer, D., W. Vith, and J. L. Unger, “Assessing particulate emissions of novel synthetic fuels and fossil fuels under different operating conditions of a marine engine and the impact of a closed-loop scrubber,” Journal of Marine Science and Engineering, vol. 12, p. 1144, 2024, doi: 10.3390/jmse12071144.
[14] Lee, J.-U., S.-C. Hwang, and S.-H. Han, “Numerical and experimental study on NOx reduction according to the load in the SCR system of a marine boiler,” Journal of Marine Science and Engineering, vol. 11, p. 777, 2023, doi: 10.3390/jmse11040777.
[15] Šenčić, T., V. Mrzljak, P. Blecich, and I. Bonefačić, “2D CFD simulation of water injection strategies in a large marine engine,” Journal of Maritime Science and Engineering, vol. 7, p. 296, 2019, doi: 10.3390/jmse7090296.
[16] Amoresano, A., G. Langella, P. Iodice, and S. Roscioli, “Numerical analysis of SO2 absorption inside a single water drop,” Atmosphere, vol. 14, p. 1746, 2023, doi: 10.3390/atmos14121746.
[17] Zannis, T. C., J. S. Katsanis, G. P. Christopoulos, E. A. Yfantis, R. G. Papagiannakis, E. G. Pariotis, D. C. Rakopoulos, C. D. Rakopoulos, and A. G. Vallis, “Marine exhaust gas treatment systems for compliance with the IMO 2020 global sulfur cap and Tier III NOx limits: A review,” Energies, vol. 15, p. 3638, 2022, doi: 10.3390/en15103638.
[18] Pelić, V., T. Mrakovčić, V. Medica-Viola, and M. Valčić, “Effect of early closing of the inlet valve on fuel consumption and temperature in a medium speed marine diesel engine cylinder,” Journal of Maritime Science and Engineering, vol. 8, no. 10, p. 747, 2020, doi: 10.3390/jmse8100747.
[19] Petrychenko, O., M. Levinskyi, S. Goolak, and V. Lukoševičius, “Prospects of solar energy in the context of greening maritime transport,” Sustainability, vol. 17, p. 2141, 2025, doi: 10.3390/su17052141.
[20] Levinskyi, M. V., and V. F. Shapo, “Adaptive control for technological type control objects,” in Advances in Intelligent Systems and Computing, vol. 1231, 2021, pp. 565–575, doi: 10.1007/978-3-030-52575-0_47.
[21] Sagin, S., O. Kuropyatnyk, O. Matieiko, R. Razinkin, T. Stoliaryk, and O. Volkov, “Ensuring operational performance and environmental sustainability of marine diesel engines through the use of biodiesel fuel,” Journal of Marine Science and Engineering, vol. 12, p. 1440, 2024, doi: 10.3390/jmse12081440.
[22] Sagin, S., O. Kuropyatnyk, and D. Rusnak, “Improvement of the process of cleaning exhaust gases of marine diesels from sulfur oxides,” Technology Audit and Production Reserves, vol. 4, no. 1(84), pp. 72–79, 2025, doi: 10.15587/2706-5448.2025.337616.
[23] Sagin, S., V. Chymshyr, S. Karianskyi, O. Kuropyatnyk, V. Madey, and D. Rusnak, “Using ultrasonic fuel treatment technology to reduce sulfur oxide emissions from marine diesel exhaust gases,” Energies, vol. 18, p. 4756, 2025, doi: 10.3390/en18174756.
[24] Kolegaev, M., and I. Brazhnik, “Improvement of the process of preparing cargo tanks of crude oil tankers for cargo operations,” Technology Audit and Production Reserves, vol. 6, no. 1(80), pp. 36–40, 2024, doi: 10.15587/2706-5448.2024.318534.
[25] Matieiko, O., “Selection of optimal schemes for the inerting process of cargo tanks of gas carriers,” Technology Audit and Production Reserves, vol. 4, no. 1(78), pp. 43–50, 2024, doi: 10.15587/2706-5448.2024.310699.
[26] Budashko, V., and V. Shevchenko, “Solving a task of coordinated control over a ship automated electric power system under a changing load,” Eastern-European Journal of Enterprise Technologies, vol. 2, no. 110, pp. 54–70, 2021, doi: 10.15587/1729-4061.2021.229033.
[27] Wang, F., J. Zhao, T. Li, P. Guan, S. Liu, H. Wei, and L. Zhou, “Research on NOx emissions testing and optimization strategies for diesel engines under low-load cycles,” Atmosphere, vol. 16, p. 190, 2025, doi: 10.3390/atmos16020190.
[28] Stoliaryk, T., “Analysis of the operation of marine diesel engines when using engine oils with different structural characteristics,” Technology Audit and Production Reserves, vol. 5, no. 1(67), pp. 22–32, 2022, doi: 10.15587/2706-5448.2022.265868.
[29] Budashko, V., A. Sandler, and V. Shevchenko, “Diagnosis of the technical condition of high-tech complexes by probabilistic methods,” TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 16, no. 1, pp. 105–111, 2022, doi: 10.12716/1001.16.01.11.
[30] Zablotsky, Y. V., “The use of chemical fuel processing to improve the economic and environmental performance of marine internal combustion engines,” Scientific Research of the SCO Countries: Synergy and Integration, 2019, doi: 10.34660/inf.2019.15.36257.
[31] Sagin, A. S., and Yu. V. Zablotskyi, “Reliability maintenance of fuel equipment on marine and inland navigation vessels,” Austrian Journal of Technical and Natural Sciences, nos. 7–8, pp. 14–17, 2021, doi: 10.29013/AJT-21-7.8-14-17.
[32] Gorb, S., M. Levinskyi, and M. Budurov, “Sensitivity optimisation of a main marine diesel engine electronic speed governor,” Scientific Horizons, vol. 24, no. 11, pp. 9–19, 2021, doi: 10.48077/scihor.24(11).2021.9-19.
[33] Maryanov, D., “Development of a method for maintaining the performance of drilling fluids during transportation by platform supply vessel,” Technology Audit and Production Reserves, vol. 5, no. 2(61), pp. 15–20, 2021, doi: 10.15587/2706-5448.2021.239437.
[34] Melnyk, O., O. Fomin, O. Shumylo, V. Yarovenko, M. Jurkovič, and V. Ocheretna, “Simulation of the interrelationship between energy efficiency and ship safety based on empirical data and regression analysis,” in Systems, Decision and Control in Energy VII (Studies in Systems, Decision and Control, vol. 596), V. Babak and A. Zaporozhets, Eds. Cham: Springer, 2025, doi: 10.1007/978-3-031-90462-2_16.
[35] Varbanets, R., O. Fomin, V. Píštěk, V. Klymenko, D. Minchev, A. Khrulev, V. Zalozh, and P. Kučera, “Acoustic method for estimation of marine low-speed engine turbocharger parameters,” Journal of Maritime Science and Engineering, vol. 9, p. 321, 2021, doi: 10.3390/jmse9030321.
[36] Lamas Galdo, M. I., L. Castro-Santos, and C. G. Rodriguez Vidal, “Numerical analysis of NOx reduction using ammonia injection and comparison with water injection,” Journal of Maritime Science and Engineering, vol. 8, no. 2, p. 109, 2020, doi: 10.3390/jmse8020109.
[37] Drazdauskas, M., and S. Lebedevas, “Numerical study on optimization of combustion cycle parameters and exhaust gas emissions in marine dual-fuel engines by adjusting ammonia injection phases,” Journal of Maritime Science and Engineering, vol. 12, p. 1340, 2024, doi: 10.3390/jmse12081340.
[38] Petrenko, T., “Study of physicochemical and geochemical aspects of enhanced oil recovery and CO2 storage in oil reservoirs,” Technology Audit and Production Reserves, vol. 2, no. 1(82), pp. 24–29, 2025, doi: 10.15587/2706-5448.2025.325343.
[39] Bian, J., L. Duan, and Y. Yang, “Simulation and economic investigation of CO2 separation from gas turbine exhaust gas by molten carbonate fuel cell with exhaust gas recirculation and selective exhaust gas recirculation,” Energies, vol. 16, p. 3511, 2023, doi: 10.3390/en16083511.
[40] Li, M., M. Qiu, Y. Li, H. Tang, R. Wu, Z. Yu, Y. Zhang, S. Ye, C. Zheng, Y. Qu, et al., “Research on ship carbon-emission monitoring technology and suggestions on low-carbon shipping supervision system,” Atmosphere, vol. 16, p. 773, 2025, doi: 10.3390/atmos16070773.
[41] Sagin, S., O. Haichenia, S. Karianskyi, O. Kuropyatnyk, R. Razinkin, A. Sagin, and O. Volkov, “Improving green shipping by using alternative fuels in ship diesel engines,” Journal of Maritime Science and Engineering, vol. 13, no. 3, p. 589, 2025, doi: 10.3390/jmse13030589.

The article presents the radar reflectivity of complex objects (navigation objects in atmospheric formations) during their observation by a shipborne radar polarisation complex (SRPC) in the form of an equation relating three matrices. Two matrices determine the energy and parametric characteristics of fully polarised waves that irradiate a complex radar observation object, the elements of which are real Stokes energy parameters, while the third matrix of Müller scattering of echo signals of partially polarised waves of a complex object determines its scattering properties, the elements of which are the effective scattering areas of the navigation object and atmospheric formation. The reflectivity of the navigation object is represented by four linear equations and allows determining the effective reflective properties of its surface by measuring the SRPC of four Stokes parameters of the reflected wave echo signals. Taking into account the scattering properties of atmospheric formations, their reflective properties are substantiated and presented in the form of a matrix consisting of 16 elements, which are the average effective scattering surfaces of atmospheric formation particles for the radar volume, and its polarisation properties are determined by four consecutive irradiations with fully polarised waves of specific polarisation and measurement of the Stokes parameters for each polarisation of the irradiating wave. The reflective properties of a complex object are considered from the point of view of distinguishing the polarisation structure of its echo signals, the individual characteristics of the observed SRPC navigation object against the background of the echo signal of atmospheric formation, and are presented in the form of a Mueller matrix.

Keywords: navigation object, atmospheric formation, complex object, radar observation, fully polarized wave, partially polarized wave, reflectivity of the communication equation, energy characteristics, parametric characteristics, scattering matrix, Stokes parameters

[1] Ryzhkov A., “The effect of nonuniform beat filling on the quality of radar polarimetric data,” in Proc. 4th Eur. Conf. on Radar in Meteorology and Hydrology (ERAD 2006), Barcelona, Sep. 18–22, 2006, pp. 1–4.
[2] Ryzhkov A., Hydak D., and Scott J., “A new polarimetric scheme for attenuation correction at C-band,” in Proc. ERAD 2006, 2006, pp. 29–32.
[3] Ryzhkov A. and Zrnic D., “The impact of depolarization on polarimetric signatures in snow,” in Proc. ERAD 2006, 2006, pp. 33–36.
[4] Hydak D., Rodriguez P., G. Lee W., Ryzhkov A., Fabry F., and Donaldson N., “Winter precipitation studies with a dual-polarized C-band radar,” in Proc. ERAD 2006, 2006, pp. 9–12.
[5] Vorobei V. I., Doronin V. V., and Rodnyansky R. A., Shipborne Navigational Radar Stations. Kyiv, Ukraine: KGAVT, 2005. [in Ukrainian].
[6] Holovin V. A. and Romanenko T. V., Radiolocation: Software Package for Calculating the Backscattering Pattern. Textbook for Students of Specialty 172 “Telecommunications and Radio Engineering”. Kyiv, Ukraine: Igor Sikorsky Kyiv Polytechnic Institute, 2021. [in Ukrainian].
[7] Malcev V. V., Sisigin I. V., and Kolesnikov K. O., “Approach to modeling radar signals reflected from objects of complex spatial configuration,” Radiopromyshlennost (Radio Industry), no. 1, pp. 42–49, 2018. [in Ukrainian].
[8] Obod I. I., Strelnytskyi O. O., and Andrusevych V. A., Information Model of Airspace Surveillance Systems. Kharkiv, Ukraine: Kharkiv National University of Radio Electronics, 2015. [in Ukrainian].
[9] Obod I. I., Chernykh O. P., Zavolodko V. V., and Tkachenko O. Yu., “Information model of airspace surveillance systems,” Information Processing Systems, no. 5(142), pp. 35–37, 2016. [in Ukrainian].
[10] Krylov E., “Prospects for the development of radar stations of the armed forces of foreign states,” Foreign Military Review, no. 2, pp. 37–40, 2018. [in Ukrainian].
[11] Korban D., “Polarization selection of navigation objects located in the zone of atmospheric formations,” Shipping & Navigation, no. 32, pp. 56–70, 2021, doi: 10.31653/2306-5761.32.2021.56-70
[12] Korban D., “Polarization method for navigation object selection in ship radar observation,” Scientific Journals of the Maritime University of Szczecin, vol. 76, pp. 148–155, 2023.
[13] Korban D., Volkov O., and Kostenko P., “Parametric polarization radiolocation method to improve radar observation of navigational objects against the background of natural clutter,” Buletinul Universității Maritime Constanța, 2018.
[14] Stetsenko M., Melnyk O., Vorokhobin I., and Ivanova I., “Polarization-based target detection approach to enhance small surface object identification ensuring navigation safety,” System Research and Information Technologies, 2024.
[15] Korban D., Melnyk O., Onyshchenko O., et al., “Radar-based detection and recognition methodology of autonomous surface vehicles in challenging marine environment,” Scientific Journal of Silesian University of Technology, Series Transport, vol. 122, pp. 111–127, 2024.

The work analyzes methods for implementing a software product that synthesizes a ship’s cargo program addressing both direct and inverse loading problems. Preparing and calculating a preliminary cargo plan is critical to seaworthiness; consequently, modern vessels employ computer cargo programs to design such plans and evaluate safety. Ships also carry documentation enabling manual calculation via interpolation tables and graphs. Yet on older ships, cargo software may be inoperable or absent, making manual planning cumbersome. Using an object-oriented approach, we argue that an effective cargo program should comprise two modules that synthesize a ship object and a cargo object. We highlight the need for object-oriented mathematical descriptions of the vessel and cargo, mapped into a computer database derived from ship cargo documentation. We further propose constructing a vector of seaworthiness criteria computed from this database. We present results from developing a module that records essential information on cargo spaces, their positions relative to the hull, and principal ship characteristics. This module supports structured data entry, consistency checks, and future expansion to optimization routines. Overall, the study motivates a database-centric, object-oriented architecture for cargo planning that can operate independently of legacy software, standardize source data, and enable synthesis, evaluation, and eventual automation of preliminary cargo plans under diverse operational conditions.

Keywords: ship’s maritime safety, object-oriented approach, ship’s cargo program, cargo plan, ship’s mathematical model, database, ship’s documentation, seaworthiness

[1] M.Z. Muis Alie, A. Ardianti, J. Juswan, T. Rachman, A. Alamsyah, N. Indah and Aulia N.S. “Ship Hull Construction Analysis to the Ultimate Strength Considering Damages”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 19, no. 2, doi:10.12716/1001.19.02.21, pp. 515-521, 2025.
[2] L.L. Nikolaieva., T.Y. Omelchenko and O.V. Haichenia. “New Approach In Models for Managing the Vessel Unloading Process”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 18, no. 4, doi:10.12716/1001.18.04.11, pp. 847-862, 2024.
[3] R. de Oliveira Bezerra, J.C.de Melo Bernardino, and R Esferra.. “Displacement Measurement System for Small-Scale Vessels Berthed in Physical Models of Port Terminals”. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 18, no. 1, doi:10.12716/1001.18.01.17, pp. 169-175, 2024.
[4] J. Kosiek, A. Kaizer, A. Salomon and A. Sacharko. “Analysis of Modern Port Technologies Based on Literature Review”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 15, no. 3, doi:10.12716/1001.15.03.22, pp. 667-674, 2021.
[5] A. Karaś, “Smart Port as a Key to the Future Development of Modern Ports”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 14, no. 1, doi:10.12716/1001.14.01.01, pp. 27-31, 2020.
[6] Ю.Ю. Васьков, ” Деякі питання оптимізації вантажних операцій навалочних суден” , Судноводіння, Вип. 6, С. 40 – 45, 2003.
[7] М.М. Цимбал, Ю.Ю. Васьков, “Формування оптимізаційної задачі проведення вантажних операцій навалочних суден “, Судноводіння, Вип. 7, С. 3 – 9, 2004.
[8] М.М. Цимбал, Ю.Ю. Васьков, “Розрахунок меж безлічі допустимих стратегій проведення вантажних операцій навалочних суден”, Судноводіння, Вип. 8, С. 22 – 31, 2004.
[9] М.Ю. Соколов, ” Метод формування вантажної програми судна з використанням раніше створеної бази даних “, Судноводіння, Вип. 18, С. 169 – 172, 2010.
[10] М.Ю. Соколов, “Методи оптимізації завантаження суден”, Судноводіння, Вип. 20,. С. 221 – 225, 2011.
[11] А.О. Чепок, “Вибір типів генеральних вантажів під час моделювання їх укладання у вантажні приміщення судна “, Судноводіння, Вип. 17, С. 233-238, 2009.
[12] А.О. Чепок, “Відображення параметрів посадки, остійності та загальної поздовжньої міцності у вантажній комп’ютерній програмі судна”, Судноводіння, Вип.19, С. 163-169, 2011.
[13] А.О. Чепок, “Розробка процедури відображення укладання генерального вантажу у трюмах судна “, Судноводіння, – Вип. 20. С. 146-149, 2011.
[14] Е.А. Власенко, “Визначення максимального значення горизонтальної складової сил інерцій, що діє на вантаж при хитавиці судна”, Science and Education a New Dimension. Natural and Technical Sciences, VI (18), Issue: 158, – С. 80-84, 2018.
[15] Е.А. Власенко, “Залежність сил інерції бортової качки від моменту інерції судна щодо поздовжньої осі “, Austria – science, Issue: 23, С. 54 – 60, 2019.
[16] Е.А. Власенко, “Допустиме завантаження контейнеровоза”, Science and Education a New Dimension. Natural and Technical Sciences, VI (22), Issue: 186, С. 87 – 94, 2018.
[17] Е.А.Власенко, Е.В.Калініченко, М.М. Цимбал, “Імітаційне моделювання завантаження контейнеровозу”, Austria – science, Issue: 26, С. 43 – 49, 2019.
[18] М.М. Цимбал, “Формування тензора завантаження контейнеровозу у разі проведення вантажних операцій у кількох портах”, Судноводіння, Вип. 29, С. 35-41, 2019.
[19] М.М. Цимбал “Розрахунок рейсового вантажного плану контейнеровозу”, Судноводіння, Вип. 30, С. 14 – 20, 2020.
[20] М.М. Цимбал, “Формування плану завантаження контейнеровозу”, Науковий вісник Херсонської державної морської академії, Вип. 2(17), С. 14 – 20, 2020.
[21] М.М. Цимбал, ” Планування завантаження контейнеровозу у разі проведення вантажних операцій у кількох портах”, Science and Education a New Dimension. Natural and Technical Sciences, VIII (27), Issue: 224, С. 71 – 73. 2020.
REFERENCES
[1] M.Z. Muis Alie, A. Ardianti, J. Juswan, T. Rachman, A. Alamsyah, N. Indah and Aulia N.S. “Ship Hull Construction Analysis to the Ultimate Strength Considering Damages”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 19, no. 2, doi:10.12716/1001.19.02.21, pp. 515-521, 2025.
[2] L.L. Nikolaieva., T.Y. Omelchenko and O.V. Haichenia. ” New Approach In Models for Managing the Vessel Unloading Process”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 18, no. 4, doi:10.12716/1001.18.04.11, pp. 847-862, 2024.
[3] R. de Oliveira Bezerra, J.C.de Melo Bernardino, and R Esferra. “Displacement Measurement System for Small-Scale Vessels Berthed in Physical Models of Port Terminals”. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 18, no. 1, doi:10.12716/1001.18.01.17, pp. 169-175, 2024.
[4] J. Kosiek, A. Kaizer, A. Salomon and A. Sacharko. “Analysis of Modern Port Technologies Based on Literature Review”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 15, no. 3, doi:10.12716/1001.15.03.22, pp. 667-674, 2021.
[5] A. Karaś, “Smart Port as a Key to the Future Development of Modern Ports”, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, vol. 14, no. 1, doi:10.12716/1001.14.01.01, pp. 27-31, 2020.
[6] Yu.Yu. Vaskov, “Some questions about the optimization of cargo operations of bulk vessels”, Sudovozhdenie, Vyp. 6, pp 40 – 45, 2003.
[7] N.N. Tsimbal, Yu.Yu. Vaskov, “Formation of the optimization task of carrying out cargo operations of bulk vessels”, Shipping&Navigation, Issue 7, pp. 3 – 9, 2004.
[8] N.N. Tsimbal, Yu.Yu. Vaskov, “Calculation of the limits of the set of allowable strategies for carrying out cargo operations of bulk vessels”, Shipping&Navigation, Issue 8, pp. 22 – 31, 2004.
[9] M.Yu. Sokolov, “The method of forming the ship’s cargo program using the previously created database “, Shipping&Navigation, Issue 18, pp. 169 – 172, 2010.
[10] M.Yu. Sokolov, “Methods of optimizing the loading of vessels”, Shipping&Navigation, Issue 20, pp. 221 – 225, 2011.
[11] A.O. Chepok, “Selection of general cargo types when modeling their stacking in the ship’s cargo spaces”, Shipping&Navigation, Issue 17, pp. 233-238, 2009.
[12] A.O. Chepok, “Display of landing parameters, stability and overall longitudinal strength in the ship’s cargo computer program”, Shipping&Navigation, Issue 19, pp. 163-169, 2011.
[13] A.O. Chepok, “Development of a procedure for displaying general cargo in the ship’s holds”, Shipping&Navigation, Issue 20, pp. 146-149, 2011.
[14] Ye.A. Vlasenko, “Determination of the maximum value of the horizontal component of the inertial forces acting on the cargo when the ship rolls”, Science and Education a New Dimension. Natural and Technical Sciences, VI (18), Issue: 158, – pp. 80- 84, 2018.
[15] Ye.A. Vlasenko, “Dependence of the forces of inertia of the side duck on the moment of inertia of the vessel relative to the longitudinal axis”, Austria – science, Issue: 23, pp. 54 – 60, 2019.
[16] Ye.A. Vlasenko, “Permissible loading of a container ship”, Science and Education a New Dimension. Natural and Technical Sciences, VI (22), Issue: 186, pp. 87 – 94, 2018.
[17] Ye.A. Vlasenko, E.V. Kalinichenko, M.N. Tsimbal, “Simulated modeling of loading a container ship”, Austria – science, Issue: 26, pp. 43 – 49, 2019.
[18] M.N. Tsimbal, “Formation of the loading tensor of a container ship in case of carrying out cargo operations in several ports”, Shipping&Navigation, Issue 29, pp. 35-41, 2019.
[19] M.N. Tsimbal, “Calculation of the voyage cargo plan of the container ship”, Shipping&Navigation, Issue 30, pp. 14 – 20, 2020.
[20] M.N. Tsimbal, “Container ship loading planning in case of carrying out cargo operations in several ports”, Science and Education a New Dimension. Natural and Technical Sciences, VIII (27), Issue: 224, pp. 71 – 73. 2020.

The study presents a methodology for combining ensemble models to forecast key parameters of a sea agent’s activity in service ergatic systems. It synthesizes boosting, stacking, and hybrid architectures with deep learning elements to handle complex nonlinear and time-series data with irregularities typical of port logistics. A modular prototype solution relies on comparative model evaluation: LightGBM, a three-component stacking ensemble (Decision Tree, Logistic Regression, SVM), and a Random Forest + LSTM hybrid. Optimization follows a risk-minimization criterion, with ensemble outputs directly informing managerial decisions. Across Accuracy, F1-score, and inverted MAE metrics, LightGBM outperformed alternatives by roughly 20%. The paper analyzes risks of operational losses due to inaccurate vessel turnaround planning and excessive berth time. Using the decision-support prototype and a derived risk-assessment concept, it offers recommendations for agents to mitigate additional berth downtime caused by delays or unpredictable congestion, thereby minimizing new operating expenses. Practically, the results enable a strategy of proactive risk reduction and resource-allocation optimization through high-precision forecasts. Theoretically, they demonstrate the viability of complex ensemble methods with a dominant boosting component for a wide range of optimal decision-support tasks in service ergatic systems under stochastic fluctuations in operational demand.

Keywords: ensemble machine learning, sea agency, decision support system, LightGBM, gradient boosting, operational risk, service ergatic systems, stacking generalization, predictive analytics, port logistics

[1] L. R. Abreu, I. S. F. Maciel, J. S. Alves, L. C. Braga, and H. L. J. Pontes, “A decision tree model for the prediction of the stay time of ships in Brazilian ports,” Engineering Applications of Artificial Intelligence, vol. 118, art. 105634, 2023, doi: 10.1016/j.engappai.2022.105634.
[2] N. Evmides, S. Aslam, T. T. Ramez, M. P. Michaelides, and H. Herodotou, “Enhancing prediction accuracy of vessel arrival times using machine learning,” Journal of Marine Science and Engineering, vol. 12, no. 8, art. 1362, 2024, doi: 10.3390/jmse12081362.
[3] Y. Li and Z. Wang, “biSAMNet: A novel approach in maritime data completion using deep learning and NLP techniques,” Journal of Marine Science and Engineering, vol. 12, no. 6, art. 868, 2024, doi: 10.3390/jmse12060868.
[4] W. Peng, X. Bai, D. Yang, K. F. Yuen, and J. Wu, “A deep learning approach for port congestion estimation and prediction,” Maritime Policy & Management, vol. 50, no. 7, pp. 835–860, 2022, doi: 10.1080/03088839.2022.2057608.
[5] Z. Chu, R. Yan, and S. Wang, “Vessel turnaround time prediction: A machine learning approach,” Ocean and Coastal Management, vol. 249, art. 107021, 2024, doi: 10.1016/j.ocecoaman.2024.107021.
[6] R. Yan, Z. Chu, L. Wu, and S. Wang, “Predicting vessel service time: A data-driven approach,” Advanced Engineering Informatics, vol. 62, art. 102718, 2024, doi: 10.1016/j.aei.2024.102718.
[7] J.-H. Yoon, S.-W. Kim, J.-S. Jo, and J.-M. Park, “A comparative study of machine learning models for predicting vessel dwell time estimation at a terminal in the Busan New Port,” Journal of Marine Science and Engineering, vol. 11, no. 10, art. 1846, 2023, doi: 10.3390/jmse11101846.
[8] Y. Yang, Y. Liu, G. Li, Z. Zhang, and Y. Liu, “Harnessing the power of machine learning for AIS data-driven maritime research: A comprehensive review,” Transportation Research Part E: Logistics and Transportation Review, vol. 183, art. 103426, 2024, doi: 10.1016/j.tre.2024.103426.
[9] S. Filom, A. M. Amiri, and S. Razavi, “Applications of machine learning methods in port operations – A systematic literature review,” Transportation Research Part E: Logistics and Transportation Review, vol. 161, art. 102722, 2022, doi: 10.1016/j.tre.2022.102722.
[10] V. Jidkov, R. Abielmona, and A. Teske, “Enabling maritime risk assessment using natural language processing-based deep learning techniques,” in Proc. IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 2469–2476, doi: 10.1109/SSCI47803.2020.9308441.
[11] М. Рудніченко, Т. Отрадська, Д. Шибаєв, І. Петров, та М. Полікарпов, «Розробка системи підтримки прийняття рішень для менеджера з управління ІТ-проектами,» Інформаційні технології та суспільство, вип. 2, с. 50–57, 2021, doi: 10.32689/maup.it.2021.2.6.
[12] М. Д. Рудніченко та І. М. Петров, «Особливості використання концепції єдиного інформаційного простору для потреб сервісних ергатичних систем на морському транспорті,» у Proc. International Multidisciplinary Conf. “Science and Technology of the Present Time: Priority Development Directions of Ukraine and Poland”, т. 1, Wołomin, Poland, 19–20 Oct. 2018, с. 106–108. Wołomin: Baltija Publishing, 2018.
[13] I. Petrov, V. Samoilenko, I. Kotelnikova, V. Tomakh, and N. Bocharova, “Leadership’s role in navigating sustainability and digitalization in enterprise,” International Journal of Organizational Leadership, vol. 12, pp. 165–182, 2023, doi: 10.33844/ijol.2023.60378.
[14] B. Wiśnicki, T. Dzhuguryan, S. Mielniczuk, I. Petrov, and L. Davydenko, “A decision support model for lean supply chain management in city multifloor manufacturing clusters,” Sustainability, vol. 16, no. 20, art. 8801, 2024, doi: 10.3390/su16208801.
[15] O. Melnyk, O. Onishchenko, and A. Zaporozhets, Eds., “Causal model and cluster analysis of marine incidents: Risk factors and preventive strategies,” in Maritime Systems, Transport and Logistics I, Studies in Systems, Decision and Control, vol. 580. Cham, Switzerland: Springer, 2025, pp. 89–105, doi: 10.1007/978-3-031-82027-4_6.
[16] O. Melnyk, O. Onishchenko, T. Melenchuk, I. Petrov, and O. Moskaliuk, “Study of the human factor influence on ergonomic management systems in maritime transport,” in Systems, Decision and Control in Energy VII, Studies in Systems, Decision and Control, vol. 596. Cham, Switzerland: Springer, 2025, pp. 337–350, doi: 10.1007/978-3-031-90462-2_20.
[17] Є. А. Петріченко, І. М. Петров, та М. Д. Рудніченко, «Реалізація інформаційної системи автоматизації виробничої діяльності морського агента у сервісній ергатичній системі,» у Проблеми розвитку морського транспорту і туризму. Частина 2: серія монографій, під ред. О. Г. Шибаєва. Одеса, Україна: КУПРІЄНКО СВ, 2020, с. 31–39.
[18] М. Д. Рудніченко та І. М. Петров, «Розробка бази даних інформаційної системи автоматизації обліку операційних дій морського агента у сервісній ергатичній системі,» у Морський транспорт і туризм: сучасний стан та перспективи розвитку. Частина 1: серія монографій «Проблеми розвитку морського транспорту і туризму», ч. 3, під ред. О. Г. Шибаєва. Одеса, Україна: КУПРІЄНКО СВ, 2021, с. 119–125.
[19] М. Рудніченко, Н. Шибаєва, Т. Отрадська, О. Потієнко, І. Шпінарева, та І. Петров, «Система оцінки та аналізу текстового контенту на базі алгоритмів машинного навчання,» у Обробка інформації в системах управління та прийняття рішень. Проблеми та рішення: монографія, за наук. ред. В. Вичужаніна (та ін.). Одеса, Україна: НУ «ОМА», 2023, с. 160–189.
[20] N. Rudnichenko, V. Vychuzhanin, D. Shvedov, T. Otradskya, and I. Petrov, “Information system for generating recommendations for risk-oriented trading strategies based on deep learning,” in Proc. 7th Workshop for Young Scientists in Computer Science & Software Engineering (CS&SE@SW 2024). Kryvyi Rih, Ukraine: Kryvyi Rih National University; Kryvyi Rih State Pedagogical University, 2024, pp. 110–119. ISSN 1613-0073. URN: urn:nbn:de:0074-3917-X. Available: https://ceur-ws.org/Vol-3917
REFERENCES
[1] L. R. Abreu, I. S. F. Maciel, J. S. Alves, L. C. Braga, and H. L. J. Pontes, “A decision tree model for the prediction of the stay time of ships in Brazilian ports,” Engineering Applications of Artificial Intelligence, vol. 118, p. 105634, 2023, doi: 10.1016/j.engappai.2022.105634.
[2] N. Evmides, S. Aslam, T. T. Ramez, M. P. Michaelides, and H. Herodotou, “Enhancing prediction accuracy of vessel arrival times using machine learning,” Journal of Marine Science and Engineering, vol. 12, no. 8, art. 1362, 2024, doi: 10.3390/jmse12081362.
[3] Y. Li and Z. Wang, “biSAMNet: A novel approach in maritime data completion using deep learning and NLP techniques,” Journal of Marine Science and Engineering, vol. 12, no. 6, art. 868, 2024, doi: 10.3390/jmse12060868.
[4] W. Peng, X. Bai, D. Yang, K. F. Yuen, and J. Wu, “A deep learning approach for port congestion estimation and prediction,” Maritime Policy & Management, vol. 50, no. 7, pp. 835–860, 2022, doi: 10.1080/03088839.2022.2057608.
[5] Z. Chu, R. Yan, and S. Wang, “Vessel turnaround time prediction: a machine learning approach,” Ocean & Coastal Management, vol. 249, art. 107021, 2024, doi: 10.1016/j.ocecoaman.2024.107021.
[6] R. Yan, Z. Chu, L. Wu, and S. Wang, “Predicting vessel service time: a data-driven approach,” Advanced Engineering Informatics, vol. 62, art. 102718, 2024, doi: 10.1016/j.aei.2024.102718.
[7] J.-H. Yoon, S.-W. Kim, J.-S. Jo, and J.-M. Park, “A comparative study of machine learning models for predicting vessel dwell time estimation at a terminal in the Busan New Port,” Journal of Marine Science and Engineering, vol. 11, no. 10, art. 1846, 2023, doi: 10.3390/jmse11101846.
[8] Y. Yang, Y. Liu, G. Li, Z. Zhang, and Y. Liu, “Harnessing the power of machine learning for AIS data-driven maritime research: A comprehensive review,” Transportation Research Part E: Logistics and Transportation Review, vol. 183, art. 103426, 2024, doi: 10.1016/j.tre.2024.103426.
[9] S. Filom, A. M. Amiri, and S. Razavi, “Applications of machine learning methods in port operations—A systematic literature review,” Transportation Research Part E: Logistics and Transportation Review, vol. 161, art. 102722, 2022, doi: 10.1016/j.tre.2022.102722.
[10] V. Jidkov, R. Abielmona, and A. Teske, “Enabling maritime risk assessment using natural language processing-based deep learning techniques,” in Proc. IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 2469–2476, doi: 10.1109/SSCI47803.2020.9308441.
[11] M. Rudnichenko, T. Otradska, D. Shybaiev, I. Petrov, and M. Polikarpov, “Rozrobka systemy pidtrymky pryiniattia rishen dlia menedzhera z upravlinnia IT-proektamy,” Informatsiini tekhnolohii ta suspilstvo, no. 2, pp. 50–57, 2021, doi: 10.32689/maup.it.2021.2.6.
[in Ukrainian]
[12] M. D. Rudnichenko and I. M. Petrov, “Osoblyvosti vykorystannia kontseptsii yedynoho informatsiinoho prostoru dlia potreb servisnykh erhatychnykh system na morskomu transporti,” in Proc. Int. Multidisciplinary Conf. “Science and Technology of the Present Time: Priority Development Directions of Ukraine and Poland”, vol. 1, Wołomin, Poland, Oct. 19–20, 2018, pp. 106–108. Wołomin: Baltija Publishing, 2018. [in Ukrainian]
[13] Petrov, V. Samoilenko, I. Kotelnikova, V. Tomakh, and N. Bocharova, “Leadership’s role in navigating sustainability and digitalization in enterprise,” International Journal of Organizational Leadership, vol. 12, pp. 165–182, 2023, doi: 10.33844/ijol.2023.60378.
[14] B. Wiśnicki, T. Dzhuguryan, S. Mielniczuk, I. Petrov, and L. Davydenko, “A decision support model for lean supply chain management in city multifloor manufacturing clusters,” Sustainability, vol. 16, no. 20, art. 8801, 2024, doi: 10.3390/su16208801.
[15] O. Melnyk, I. Petrov, T. Melenchuk, A. Zaporozhets, S. Bugaeva, and O. Rossomakha, “Causal model and cluster analysis of marine incidents: Risk factors and preventive strategies,” in Maritime Systems, Transport and Logistics I, O. Melnyk, O. Onishchenko, and A. Zaporozhets, Eds., Studies in Systems, Decision and Control, vol. 580. Cham, Switzerland: Springer, 2025, pp. 89–105, doi: 10.1007/978-3-031-82027-4_6.
[16] O. Melnyk, O. Onishchenko, T. Melenchuk, I. Petrov, and O. Moskaliuk, “Study of the human factor influence on ergonomic management systems in maritime transport,” in Systems, Decision and Control in Energy VII, V. Babak and A. Zaporozhets, Eds., Studies in Systems, Decision and Control, vol. 596. Cham, Switzerland: Springer, 2025, pp. 337–350, doi: 10.1007/978-3-031-90462-2_20.
[17] Ye. A. Petrichenko, I. M. Petrov, and M. D. Rudnichenko, “Realizatsiia informatsiinoi systemy avtomatyzatsii vyrobnychoi diialnosti morskoho ahenta u servisnii erhatychnii systemi,” in Problemy rozvytku morskogo transportu i turyzmu. Chastyna 2: seriia monohrafii, O. H. Shybaiev, Ed. Odesa, Ukraine: KUPRIENKO SV, 2020, pp. 31–39. [in Ukrainian]
[18] M. D. Rudnichenko and I. M. Petrov, “Rozrobka bazy danykh informatsiinoi systemy avtomatyzatsii obliku operatsiinykh dii morskoho ahenta u servisnii erhatychnii systemi,” in Morskyi transport i turyzm: suchasnyi stan ta perspektyvy rozvytku. Chastyna 1: seriia monohrafii «Problemy rozvytku morskogo transportu i turyzmu», ch. 3, O. H. Shybaiev, Ed. Odesa, Ukraine: Kupriienko SV, 2021, pp. 119–125. [in Ukrainian]
[19] M. Rudnichenko, N. Shybaieva, T. Otradska, O. Potiienko, I. Shpinareva, and I. Petrov, “Systema otsinky ta analizu tekstovoho kontentu na bazi alhorytmiv mashynnoho navchannia,” in Obrobka informatsii v systemakh upravlinnia ta pryiniattia rishen. Problemy ta rishennia: monohrafiia, V. Vychuzhanin, Sci. Ed. Odesa, Ukraine: NU “OMA,” 2023, pp. 160–189.
[in Ukrainian]
[20] N. Rudnichenko, V. Vychuzhanin, D. Shvedov, T. Otradskya, and I. Petrov, “Information system for generating recommendations for risk-oriented trading strategies based on deep learning,” in Proc. 7th Workshop for Young Scientists in Computer Science & Software Engineering (CS&SE@SW 2024), Kryvyi Rih, Ukraine, 2024, pp. 110–119. URN: urn:nbn:de:0074-3917-X. Available: https://ceur-ws.org/Vol-3917

The occurrence of added masses and moments is caused by a layer of water moving with the ship during maneuvers, which significantly increases the ship’s effective mass and affects inertial forces and moments. This effect appears as an additional term in the kinetic energy of the hull–fluid system, accounting for the water’s kinetic energy. The energy is determined by added masses along coordinate axes, cross-coupled added masses, added moments about the axes, and added static moments. For planar motion of a surface ship, four quantities are non-zero: longitudinal and transverse added masses, the added moment about the ship’s axis of rotation, and the static moment from displacement of transverse added masses. In mathematical models of ship motion, dimensional values are converted to dimensionless coefficients of added masses and moments. Studies show that, even in deep water, added masses and moments can nearly double inertial force and moment components, making their accurate determination crucial for predicting ship motion. Numerous theoretical and experimental works have developed empirical models for estimation, but significant discrepancies exist among results. This study rigorously assesses the possible range of variation of added masses and moments during ship maneuvers in deep water, analyzes existing models, and proposes an efficient empirical model for their determination.

Keywords: added masses, added moments of the ship hull, ship maneuvers, empirical formulas

[1] Pershytz R. Y., Upravlyaemost’ i upravlenie sudnom [Dynamic control and handling of the ship]. L.: Sudostroenie, 1983.
[2] Sobolev G. V., Upravlyaemost’ korablya i avtomatizatsiya sudovozhdeniya [Ship handling and navigation automation]. L.: Sudostroenie, 1976.
[3] Gofman A. D., Propulsion and steering complex and ship maneuvering: handbook. L.: Sudostroyenie, 1988.
[4] Vasil’ev A. V., Upravlyaemost’ sudov [Ship handling]. L.: Sudostroyenie, 1989.
[5] Remez Yu. V., Kachka korablya [Ship rolling]. L.: Sudostroyenie, 1983.
[6] Pavlenko V. G., Khodkost’ i upravlyaemost’ sudov [Navigability and controllability of ships]. Transport, 1991.
[7] Miyusov M. V., Modes of operation and automation of motor vessel propulsion unit with wind propulsors. Odesa, Ukraine: OGMA; OKFA, 1996.
[8] Kryvyi O. F., Methods of mathematical modeling in navigation. Odesa, Ukraine: ONMA, 2015. [in Ukrainian].
[9] Ogawa A., Koyama T., Kijima K., “MMG report-I: on the mathematical model of ship manoeuvring,” Bull. Soc. Naval Archit. Jpn., no. 575, pp. 22–28, 1977. [in Japanese].
[10] Ogawa A., Kasai H., “On the mathematical method of manoeuvring motion of ships,” Int. Shipbuild. Prog., vol. 25, no. 292, pp. 306–319, 1978.
[11] Matsumoto K., Suemitsu K., “The prediction of manoeuvring performances by captive model tests,” J. Kansai Soc. Naval Archit. Jpn., no. 176, pp. 11–22, 1980. [in Japanese].
[12] Inoue S, Hirano M., Kijima K., Takashina J., “A practical calculation method of ship maneuvering motion,” Int. Shipbuild. Prog., vol. 28, no. 325, pp. 207–222, 1981.
[13] Inoue S, Hirano M., Kijima K., “Hydrodynamic derivatives on ship manoeuvring,” Int. Shipbuild. Prog., vol. 28, no. 321, p. 67, 1981.
[14] Yoshimura Y., Masumoto Y., “Hydrodynamic database and manoeuvring prediction method with medium high-speed merchant ships and fishing vessels,” in Proc. Int. Conf. Marine Simulation and Ship Manoeuvrability (MARSIM 2012), 2012, pp. 494–504
[15] Yoshimura Y., Ma N., “Manoeuvring prediction of fishing vessels,” in Proc. MARSIM ’03, 2003, pp. RC-29-1–RS-29-10.
[16] Yoshimura Y., Masumoto Y., “Hydrodynamic force database with medium high speed merchant ships including fishing vessels and investigation into a manoeuvring prediction method,” J. Japan Soc. Naval Architects Ocean Eng., vol. 14, pp. 63–73, 2011, doi: 10.2534/jjasnaoe.14.6
[17] Yasukawa H., Yoshimura Y., “Introduction of MMG standard method for ship maneuvering predictions,” J. Mar. Sci. Technol., vol. 20, pp. 37–52, 2015, doi: 10.1007/s00773-014-0293-y
[18] Yasukawa H., Sakuno R., “Application of the MMG method for the prediction of steady sailing condition and course stability of a ship under external disturbances,” J. Mar. Sci. Technol., vol. 25, pp. 196–220, 2020, doi: 10.1007/s00773-019-00641-4
[19] Ayub F.A., Furukawa Y., “Comparison between cubic and quadratic models of hydrodynamic derivatives to the ship course stability index,” Int. J. Technol., vol. 15, no. 5, pp. 1502–1523, 2024, doi: 10.14716/ijtech.v15i5.7036
[20] Kryvyi O. F., Miyusov M. V., “Mathematical model of movement of the vessel with auxiliary wind-propulsors,” Shipping & Navigation, vol. 26, pp. 110–119, 2016.
[21] Kryvyi O. F., Miyusov M. V., “Construction and analysis of mathematical models of hydrodynamic forces and moment on the ship’s hull using multivariate regression analysis,” TransNav, Int. J. Marine Navigation Saf. Sea Transp., vol. 15, no. 4, pp. 853–864, 2021, doi: 10.12716/1001.15.04.18
[22] Kryvyi O. F., Miyusov M. V., “Mathematical model of hydrodynamic characteristics on the ship’s hull for any drift angles,” in Advances in Marine Navigation and Safety of Sea Transportation. Boca Raton, FL, USA: CRC Press, 2019, pp. 111–117, doi: 10.1201/9780429341939
[23] Kryvyi O., Miyusov M. V., Kryvyi M., “Construction and analysis of new mathematical models of the operation of ship propellers in different maneuvering modes,” TransNav, Int. J. Marine Navigation Saf. Sea Transp., vol. 17, no. 1, pp. 853–864, 2023, doi: 10.12716/1001.17.01.09
[24] Kryvyi O., Miyusov M. V., Kryvyi M., “Analysis of known and construction of new mathematical models of forces on a ship’s rudder in an unbounded flow analysis,” TransNav, Int. J. Marine Navigation Saf. Sea Transp., vol. 17, no. 4, pp. 831–839, 2023, doi: 10.12716/1001.17.04.09
[25] Yoshimura Y., Nakamura M., Taniguchi T., and Yasukawa H., “Empirical formulas of hydrodynamic parameters for predicting ship maneuvering based on the MMG-model,” Ocean Eng., vol. 337, p. 121831, 2025, doi: 10.1016/j.oceaneng.2025.121831
[26] Wendel K., “Hydrodynamische Massen und hydrodynamische Massenträgheitsmomente,” Jahrb. Schiffbautechn. Ges., vol. 44, pp. 207–255, 1950. [in German].
[27] Korotkin A. I., Added Masses of Ship Structures. Dordrecht, The Netherlands: Springer, 2009, doi: 10.1007/978-1-4020-9432-3
[28] Motora S., “On the measurement of added mass and added moment of inertia of ships in steering motion,” in Proc. 1st Symp. Ship Manoeuvrability, David Taylor Model Basin Rep. 1461, Washington, DC, USA, 1960.
[29] Motora S., “On the measurement of added mass and added moment of inertia for ship motions,” J. Zosen Kiokai, no. 105, pp. 83–92, 1959. [in Japanese].
[30] Motora S., “On the measurement of added mass and added moment of inertia for ship motions: part 2. Added mass for the longitudinal motions,” J. Zosen Kiokai, no. 106, pp. 59–62, 1960. [in Japanese].
[31] Clarke D. et al., “The application of manoeuvring criteria in hull design using linear theory,” in Spring Meeting of the Royal Institution of Naval Architects, 1982.
[32] Hooft J.P., Pieffer J.B.M., “Manoeuvrability of frigates in waves,” Mar. Technol., vol. 25, 1988.
[33] Zhou Z., Yan S., Feng W., “Maneuvering prediction of multiple-purpose cargo ships,” Ship Eng., vol. 6, pp. 21–36, 1983. [in Chinese].
[34] Sadakane H., Toda Y., Lee Y.-S., “The simplified formulas to predict the coefficients of added mass and yaw added moment of inertia of a ship in shallow water,” J. Japan Inst. Navigation, pp. 11–20, 2001.
[35] Schneekluth H., and Bertram V., Ship Design for Efficiency and Economy, 2nd ed. Oxford, U.K.: Butterworth-Heinemann, 1998.
[36] ITTC, “Appendix A: Manoeuvring in shallow and confined waters,” in Proc. 23rd Int. Towing Tank Conf., vol. 1, Venice, Italy, 2002, pp. 201–234.