Prediction of DEDI index for meteorological drought with the VMD-CBiLSTM hybrid model-Reference-Cited by-同舟云学术

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Prediction of DEDI index for meteorological drought with the VMD-CBiLSTM hybrid model

Published:2024-09 Issue: Volume:641 Page:131805
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Su Tao,Liu Dan,Cui Xingyuan,Dou Xianshen,Lei Bo,Cheng Xu,Yuan Mengning,Chen Renjie

Funder

Anhui University of Science and Technology

Environmentally Friendly Materials and Occupational Health Research Institute, Anhui University of Science and Technology

Publisher

Elsevier BV

Reference58 articles.

1. Estimation of ARIMA model parameters for drought prediction using the genetic algorithm;Abbasi;Arab. J. Geosci.,2021

2. Machine learning in weather prediction and climate analyses—applications and perspectives;Bochenek;Atmos.,2022

3. Outlier detection in large data sets;Buzzi-Ferraris;Comput. Chem. Eng.,2011

4. Machine learning emulation of gravity wave drag in numerical weather forecasting;Chantry;J. Adv. Model. Earth Syst.,2021

5. Deep-STEP: A deep learning approach for spatiotemporal prediction of remote sensing data;Das;IEEE Geosci. Remote Sens. Lett.,2016

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