The wave state plays a vital role in the planning of marine activities. Predicting the wave significant height can prepare for the abnormal sea state in advance, which is of crucial influence to the marine activities. Unlike other scholars in the field of ocean research, this paper starting with analyzing artificial neural network model. By using the convolution neural network to model the measured wave height historical data, and to predict the ocean wave situation in the next six hours based on the measured data of wave height in the Beibu Gulf sea area. Using MAE, RMSE, PCC and etc. error evaluation methods, analyse the influence of convolution neural network on wave height prediction results in different layers is discussed and analyzed under different historical data input conditions. Finally, the network model is trained with the measured data in November and December 2018, and the results are analysed and compared.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.