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
Real-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship's navigation. This paper investigates the real-time prediction method of hull girder loads based on the...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | International Journal of Naval Architecture and Ocean Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2092678224000062 |
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| _version_ | 1849219951288647680 |
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| author | Qiang Wang Pengyao Yu Mingdong Lv Xiangcheng Wu Chenfeng Li Xin Chang Lihong Wu |
| author_facet | Qiang Wang Pengyao Yu Mingdong Lv Xiangcheng Wu Chenfeng Li Xin Chang Lihong Wu |
| author_sort | Qiang Wang |
| collection | DOAJ |
| description | Real-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship's navigation. This paper investigates the real-time prediction method of hull girder loads based on the Recurrent Neural Network (RNN) model and error correction strategy. Firstly, taking the vertical bending moment, horizontal bending moment, and torsional moment at the mid-ship position of a large container ship as examples, corresponding neural network prediction models are established through parameter influence analysis. Secondly, various sea state conditions are used to verify the feasibility of established network prediction models to predict the hull girder loads in real-time. The VBM prediction model performs better than the TM prediction model and HBM prediction model, and the errors of the TM prediction model and HBM prediction model are slightly larger in some cases. Lastly, an improved prediction model based on an error correction strategy is proposed to improve the prediction accuracy of the neural network prediction model, and the adequate performance of the error correction strategy is discussed. |
| format | Article |
| id | doaj-art-aee3f8437d2b4ebab005e9b48e459c79 |
| institution | Kabale University |
| issn | 2092-6782 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Naval Architecture and Ocean Engineering |
| spelling | doaj-art-aee3f8437d2b4ebab005e9b48e459c792024-12-25T04:21:05ZengElsevierInternational Journal of Naval Architecture and Ocean Engineering2092-67822024-01-0116100587Real-time prediction of wave-induced hull girder loads for a large container ship based on the recurrent neural network model and error correction strategyQiang Wang0Pengyao Yu1Mingdong Lv2Xiangcheng Wu3Chenfeng Li4Xin Chang5Lihong Wu6College of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, ChinaCollege of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, China; Corresponding author.College of Navigation, Dalian Naval Academy, Dalian, ChinaCollege of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, ChinaCollege of Shipbuilding Engineering, Harbin Engineering University, Harbin, ChinaCollege of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, ChinaCollege of Naval Architecture and Ocean Engineering, Dalian Maritime University, Dalian, ChinaReal-time acquisition of wave-induced hull girder loads of a sailing ship will help the captain make reasonable decisions, which is of great significance for improving the safety of the ship's navigation. This paper investigates the real-time prediction method of hull girder loads based on the Recurrent Neural Network (RNN) model and error correction strategy. Firstly, taking the vertical bending moment, horizontal bending moment, and torsional moment at the mid-ship position of a large container ship as examples, corresponding neural network prediction models are established through parameter influence analysis. Secondly, various sea state conditions are used to verify the feasibility of established network prediction models to predict the hull girder loads in real-time. The VBM prediction model performs better than the TM prediction model and HBM prediction model, and the errors of the TM prediction model and HBM prediction model are slightly larger in some cases. Lastly, an improved prediction model based on an error correction strategy is proposed to improve the prediction accuracy of the neural network prediction model, and the adequate performance of the error correction strategy is discussed.http://www.sciencedirect.com/science/article/pii/S2092678224000062Recurrent neural networkHull girder loadsShip motionsError correction strategy |
| spellingShingle | Qiang Wang Pengyao Yu Mingdong Lv Xiangcheng Wu Chenfeng Li Xin Chang Lihong Wu 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 Recurrent neural network Hull girder loads Ship motions Error correction strategy |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | Recurrent neural network Hull girder loads Ship motions Error correction strategy |
| url | http://www.sciencedirect.com/science/article/pii/S2092678224000062 |
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