Typhoon track prediction based on LSTM network

Xiangyun Wang; Yutao Yao; Xiuhuan Ding

doi:10.1117/12.2645938

23 August 2022 Typhoon track prediction based on LSTM network

Xiangyun Wang, Yutao Yao, Xiuhuan Ding

Proceedings Volume 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022); 123050Z (2022) https://doi.org/10.1117/12.2645938
Event: International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 2022, Hangzhou, China

Abstract

Typhoon is a common natural disaster, easy to harm the lives and property safety of people in coastal areas of China, so it is of great significance to accurately predict the path of typhoon. In this paper, the LSTM neural network algorithm is used to dynamically predict the typhoon path considering the longitude and latitude, central pressure, wind speed and typhoon intensity. The historical typhoon data of China National Meteorological Network are used for training and forecasting, and the error points in training and forecasting process and improvement measures are introduced in detail. The LSTM network model used in this paper can use the 24-hour typhoon data to predict the typhoon path at the next moment. Compared with THE RNN model, the accuracy has been further improved.

Citation Download Citation

Xiangyun Wang, Yutao Yao, and Xiuhuan Ding "Typhoon track prediction based on LSTM network", Proc. SPIE 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 123050Z (23 August 2022); https://doi.org/10.1117/12.2645938

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