![]() ![]() There is a space missing on L47 before Zhao et al., 2019.Ĥ. et al., 2020) does not follow the format of the other references. This will allow for readers to focus on the results section which should be the manuscript's centrepiece.Ģ. These can be either reduced significantly or placed within a supplement to join the manuscript. ![]() The introduction of the model and its settings is very detailed but far too long as it consumes the first 13 pages and 6 pages of the article. The paper is of use to the community and while I have no technical objections, there are, however, a few issues the authors should consider. considered the adoption of a joint VMD-TCN-LSTM algorithm to forecast significant wave height and wave period with minor computational expense and using direct buoy observations. In the 48-hour APD forecasts, the VMD and TCN improved the determination coefficient by 119.7 % and 40.9 %, respectively.Ĭonsidering the need to enhance predictions of ocean wave parameters, Ji et al. In the 48-hour SWH forecasts, the VMD and TCN improved the determination coefficient by 132.5 % and 36.8 %, respectively. The contribution of the TCN to the improvement of the prediction result determination coefficient gradually increased as the forecasting length increased. In the 12-, 24-, and 48-hour wave forecasts, both VMD and TCN improved the model performance. In the 3-hour wave forecasts, VMD primarily improved the model performance, while the TCN had less influence. The VMD-TCN-LSTM model has significant superiority and shows robustness and generality in different buoy prediction experiments. The VMD-TCN-LSTM model was compared with the VMD-LSTM (without TCN cells) and LSTM (without VMD and TCN cells) models. Then the SWH and APD prediction models were established using TCN, LSTM, and Bayesian hyperparameter optimization. ![]() The wave sequence features were obtained using VMD technology based on the wave data from the National Data Buoy Center. The present work proposes a prediction model of significant wave height (SWH) and average wave period (APD) based on variational mode decomposition (VMD), temporal convolutional networks (TCN), and long short-term memory (LSTM) networks. ![]()
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