河川技術論文集
Online ISSN : 2436-6714
ディープラーニングによる新しい降水予測手法の検討
金子 凌仲吉 信人
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ジャーナル フリー

2019 年 25 巻 p. 115-120

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Heavy rainfall has been causing many dreadful disasters, but its prediction is quite difficult in current weather forecast models. Today deep learning breakthrough in various field. We attempted to apply a deep learning algorithm, or stacked LSTMs, to rainfall prediction. Our LSTM weather prediction model was established with micro climate data in Kyusyu from 1990 to 2015 and validated for 2016-2018 rainfall events. The model was able to predict even weak rainfall but showed disadvantage for heavy rain fall events as well as rainfall onset prediction. We also suggested possible solutions for increasing reliability of LSTM rainfall models.

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© 2019 土木学会
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