References
- Ge S, Zeng J, Jin B, Zhou W, Qin X. Design wave calculation of a passenger catamaran under multiple load control parameters. Polish Maritime Research, 2022, 29(2), 3-11. https://doi.org/10.2478/pomr-2022-0011
- Mazarakos T, Tsaousis T. Hydrodynamic loads on a semi-submersible platform supporting a wind turbine under a mooring system with buoys. Polish Maritime Research, 2024, 31(1), 24-34. https://doi.org/10.2478/pomr-2024-0003
- Chen Z, Yu C, Dong P. Rankine source method analysis for nonlinear hydroelastic responses of a container ship in regular oblique waves. Ocean Engineering, 2019, 187, 106168. https://doi.org/10.1016/j.oceaneng.2019.106168
- Jiao J, Chen C, Ren H. Investigation of ship motions and wave loads in short-crested waves by frequency-domain hydroelasticity theory and experiment. Journal of Ship Mechanics, 2020, 24(4), 427-438. https://doi.org/10.3969/j.issn.1007-7294.2020.04.002
- Zylinski B. Finite element local analysis of wave slamming on offshore structure. Polish Maritime Research, 2009, 16(1), 8-12. https://doi.org/10.2478/v10012-008-0004-x
- Veic D, Sulisz W. Impact pressure distribution on a monopile structure excited by irregular breaking wave. Polish Maritime Research, 2018, 25(1), 29-35. https://doi.org/10.2478/pomr-2018-0019
- Lakshmynarayanana PAK, Hirdaris S. Comparison of nonlinear one-and two-way FFSI methods for the prediction of the symmetric response of a containership in waves. Ocean Engineering, 2020, 203,107179. https://doi.org/10.1016/j.oceaneng.2020.107179
- Liu G. Research on the nonlinear ship hydro-elasticity based on CFD-FEM two-way coupling method. Masters thesis. Dalian University of Technology, 2021.
- Jiao J, Huang S, Wang S, Soares CG. A CFD–FEA twoway coupling method for predicting ship wave loads and hydroelastic responses. Applied Ocean Research, 2021, 117, 102919. https://doi.org/10.1016/j.apor.2021.102919
- Huang S, Jiao J, Soares CG. Uncertainty analyses on the CFD–FEA co-simulations of ship wave loads and whipping responses. Marine Structures, 2022, 82, 103129. https://doi.org/10.1016/j.marstruc.2021.103129
- Cepowski T. Application of artificial neural networks to approximation and identification of sea-keeping performance of a bulk carrier in ballast loading condition. Polish Maritime Research, 2007, 14(4), 31-39. https://doi.org/10.2478/v10012-007-0037-6
- Sun Q, Tang Z, Gao J, Zhang G. Short-term ship motion attitude prediction based on LSTM and GPR. Applied Ocean Research, 2022, 118, 102927. https://doi.org/10.1016/j.apor.2021.102927
- Chao L. Research on ship wave load forecast method based on long short term memory network algorithm. Masters thesis. Harbin Engineering University, 2021.
- Wang Q, Yu P, Lv M,Wu X, Li C, Chang X, Wu L. Real-time prediction of wave-induced hull girder loads for a large container ship based on the recurrent neural network model and error correction strategy. International Journal of Naval Architecture and Ocean Engineering, 2024, 16, 100587. https://doi.org/10.1016/j.ijnaoe.2024.100587
- Tang H, Zhu R, Wan Q,Ren D,. Short-term prediction of trimaran load based on data driven technology. Brodogradnja, 2025, 76(1), 1-26. https://doi.org/10.21278/brod76101
- Shi W, Guo Z, Chen M, Li S, Hu J, Dai Z. Multi-step prediction of ship heave motion using transformer-enhanced multi-scale CNN. Measurement, 2025, 242, 115787. https://doi.org/10.1016/j.measurement.2024.115787
- Yan H, Chu Z, Tang J. A short-term ship motion prediction method based on quaternions and transformer-LSTM model. Ocean Engineering, 2025, 342, 122874. https://doi.org/10.1016/j.oceaneng.2025.122874
- Hochreiter S, Schmidhuber J. Long short-term memory. Neural Computation, 1997, 9(8), 1735-1780. https://doi.org/10.1162/neco.1997.9.8.1735
- Chen Z, Liu X, Ji X, Gui H. Real-time prediction of multi-degree-of-freedom ship motion and resting periods using LSTM networks. Journal of Marine Science and Engineering, 2024, 12(9), 1591. https://doi.org/10.3390/jmse12091591
- Zhao H, Wang Z, Wang G, Yu F. Dynamic chaos unveiled: enhancing ship’s attitude time series prediction through spatiotemporal embedding and improved transformer model. Measurement Science and Technology, 2024, 35(11), 116306. https://doi.org/10.1088/1361-6501/ad6687
- Li G, Tang G, Zhang J, Sun Q, Liu X. Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model. Journal of Marine Science and Engineering, 2025, 13(6), 1008. https://doi.org/10.3390/jmse13061008
- Tang H, Zhu R, Wan Q, Ren D,Meng J. Prediction of Ship Structure Response Signal Based on Bo-LSTM Neural Network. Proceedings of IEEE International Conference on Unmanned Systems, 2023, 276-280. https://doi.org/10.1109/icus58632.2023.10318384
- Sengupta D, Datta R, Sen D. A simplified approach for computation of nonlinear ship loads and motions using a 3D time-domain panel method. Ocean Engineering, 2016, 117(1), 99-113. https://doi.org/10.1016/j.oceaneng.2016.03.039
- Jiao J, Huang S, Soares CG. Viscous fluid–flexible structure interaction analysis on ship springing and whipping responses in regular waves. Journal of Fluids and Structures, 2021, 106, 103354. https://doi.org/10.1016/j.jfluidstructs.2021.103354
- Liu X, Yang J, Wu D, Hou L, Li X, Wan Q. Numerical Analysis of Resistance Characteristics of a Novel High-Speed Quadramaran. Polish Maritime Research, 2023, 30(2), 11-27. https://doi.org/10.2478/pomr-2023-0018
- Fonseca N, Soares CG. Experimental investigation of the nonlinear effects on the vertical motions and loads of a containership in regular waves. Journal of Ship Research, 2004, 48(2), 118-147. https://doi.org/10.5957/jsr.2004.48.2.118