Deep Learning for Seasonal Prediction of Summer Precipitation Levels in Eastern China
Peirong Lu,
Qimin Deng,
Shuyun Zhao
et al.
Abstract:Skilled seasonal forecasting will effectively reduce the economic losses caused by droughts and floods. Because of the powerful data mining capability of deep learning networks, it is increasingly applied in studies of seasonal rainfall prediction. However, there remain two prominent issues in the modeling process: the lack of enough training samples and the effect of a small number of extreme values on the model optimization. To tackle these deficiencies, we combine strategies such as principal component anal… Show more
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