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8 November 2023 The application of NARX neural network model based on wavelet analysis for tide level prediction
Lianbo Li, Fangjie Wang, Wenhao Wu, Honglei Qin, Zhenyu Zhu, Zhengqian Li
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Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 1292314 (2023) https://doi.org/10.1117/12.3011359
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China
Abstract
Tidal prediction is of great significance to the production and practice of coastal areas. In order to improve the accuracy of tidal level prediction, a nonlinear exogenous autoregressive network tidal prediction model (DWT-NARX) based on wavelet analysis is proposed. The model decomposes the tidal data by wavelet and realizes hierarchical prediction by NARX neural network. The tidal prediction simulation experiment is carried out by using the measured tidal data of Savannah Port in the United States. The prediction results are compared with the modular NARX tidal prediction (HANARX) model. The results show that the MAE, MSE and RMSE of the prediction results of this method are the smallest. The results show that the accuracy and stability of this method are better than the modular prediction of NARX.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Lianbo Li, Fangjie Wang, Wenhao Wu, Honglei Qin, Zhenyu Zhu, and Zhengqian Li "The application of NARX neural network model based on wavelet analysis for tide level prediction", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 1292314 (8 November 2023); https://doi.org/10.1117/12.3011359
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KEYWORDS
Neural networks
Wavelets
Data modeling
Education and training
Artificial neural networks
Atmospheric modeling
Error analysis
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