Ship motion attitude prediction model based on IWOA-TCN-Attention
Aiming at the problem of low prediction accuracy of ship motion with the characteristics of non-stationary, nonlinear and stochastic, this paper proposes a combined prediction model of ship motion based on improved whale optimization algorithm, temporal convolutional networks and attention mechanism...
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| Vydáno v: | Ocean engineering Ročník 272; s. 113911 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Ltd
15.03.2023
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| Témata: | |
| ISSN: | 0029-8018 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Aiming at the problem of low prediction accuracy of ship motion with the characteristics of non-stationary, nonlinear and stochastic, this paper proposes a combined prediction model of ship motion based on improved whale optimization algorithm, temporal convolutional networks and attention mechanism (IWOA-TCN-Attention). One research direction of ship motion prediction is to use time series for regression prediction. The TCN model is used in the research of time series prediction because of its long-term memory of time series. IWOA-TCN-Attention model firstly establishes a deep learning network based on TCN model, uses this network to obtain the original features of ship motion attitude time series data, and then gives different weight values to different original features through attention mechanism, so as to highlight important features and reduce the impact of secondary features on prediction results. At the same time, in order to further optimize the prediction accuracy of TCN-Attention model, this paper proposes an IWOA optimization algorithm by improving the WOA optimization algorithm. This algorithm is used to optimize the super parameters of TCN-Attention model, and finally obtain the optimal prediction effect. The simulation experiment shows that IWOA-TCN-Attention model can effectively realize the prediction of ship motion, reduce the error of motion prediction and improve the prediction accuracy.
•This paper proposes a ship motion attitude prediction model based on IWOA-TCN-Attention. Compared with other prediction models, this model has higher prediction accuracy.•This paper improves the whale optimization algorithm from two aspects. The improved algorithm is more capable of parameter optimization.•IWOA algorithm is used to optimize the parameters of TCN model. Experiments show that IWOA algorithm improves the accuracy of ship motion attitude prediction results.•In the traditional TCN model, the attention mechanism is added. The results show that the new model has higher prediction accuracy than the single TCN model.•The IWOA-TCN-Attention prediction model proposed in this paper is universal. It is not only applicable to ship motion prediction, but also applicable to stock price prediction and other fields. |
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| ISSN: | 0029-8018 |
| DOI: | 10.1016/j.oceaneng.2023.113911 |