Study on SPEI index distribution and simplified estimation model in Zhejiang Province
In order to obtain the drought trend and simplified estimation model of Zhejiang Province,the standardized precipitation evapotranspiration index(SPEI)of 9 stations in Zhejiang Province was calculated,and the convolutional bidirectional long short-term memory neural network model(CNN-BiLSTM)was used as the basis.Dung Beetle Algorithm(DBO)and Jean Caranx algorithm(GTO)optimized by wavelet transform(WPT)were used to construct two optimal combination models,and the accuracy of different models was compared.The results showed that the spring drought gradually intensified throughout the year,and the WPT-DPO-CNN-BiLSTM model had the highest accuracy among all models,and could be recommended for predicting the SPEI index of different scales in the whole region.
万方数据
维普
