Chen, S.; Jiang, C.; Wang, Z.; Zhang, F.; Xia, J., and Li, F., 2023. Intelligent prediction method for linear wave load based on deep neural network. Journal of Coastal Research, 39(6), 1158–1169. Charlotte (North Carolina), ISSN 0749-0208.
To more efficiently and accurately calculate the linear wave load response of a ship at any section position under different speeds, wave periods, wave heights, and wave directions, a linear wave load intelligent prediction (LWLIP) method is established by combining the experimental design, data processing and analysis, strip theory, and deep neural network methods. Taking a ship as an example, the LWLIP analysis was carried out, and the application of the LWLIP method was verified. The results show that, under any sea conditions, the LWLIP method is an alternative to the strip theory program for wave load prediction with high accuracy, it expands the calculation limitations of strip theory, such as section position and wave angle, and it improves the calculation efficiency. The prediction time of the model is 1 ms. The results of this study are of great significance for the rapid assessment of ship global wave loads.