Application of a Hybrid CEEMD-LSTM Model Based on the Standardized Precipitation Index for Drought Forecasting: The Case of the Xinjiang Uygur Autonomous Region, China

Application of a Hybrid CEEMD-LSTM Model Based on the Standardized Precipitation Index for Drought Forecasting: The Case of the Xinjiang Uygur Autonomous Region, China

Accurate forecasting of droughts can effectively reduce the risk of drought. We propose a hybrid model based on complementary ensemble empirical mode decomposition (CEEMD) and long short-term memory (LSTM) to improve drought prediction accuracy. Taking the Xinjiang Uygur Autonomous Region as an exam...

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Bibliographic Details
Main Authors: Yan Ding, Guoqiang Yu, Ran Tian, Yizhong Sun
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Atmosphere
Subjects:
drought forecasting
complementary ensemble empirical mode decomposition
long short-term memory
standardized precipitation index
Online Access:https://www.mdpi.com/2073-4433/13/9/1504

Internet

https://www.mdpi.com/2073-4433/13/9/1504

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