Wind speed prediction of unmanned sailboat based on CNN and LSTM hybrid neural network

Author:

Shen Zhipeng,Fan Xuechun,Zhang Liangyu,Yu HaomiaoORCID

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Doctoral Start-up Foundation of Liaoning Province

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Ocean Engineering,Environmental Engineering

Reference42 articles.

1. Linear and non-linear autoregressive models for short-term wind speed forecasting;A;Energy Convers. Manage.,2016

2. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al., 2016. {TensorFlow}: A system for {Large−Scale} machine learning. In: 12th USENIX Symposium on Operating Systems Design and Implementation. OSDI 16, pp. 265–283.

3. A multi-scale model based on the long short-term memory for day ahead hourly wind speed forecasting;Araya;Pattern Recognit. Lett.,2020

4. Forecasting of COVID-19 using deep layer recurrent neural networks (RNNs) with gated recurrent units (GRUs) and long short-term memory (LSTM) cells;ArunKumar;Chaos Solitons Fractals,2021

5. Learning long-term dependencies with gradient descent is difficult;Bengio;IEEE Trans. Neural Netw.,1994

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