Comparison of LSTM network, neural network and support vector regression coupled with wavelet decomposition for drought forecasting in the western area of the DPRK-Reference-Cited by-同舟云学术

Comparison of LSTM network, neural network and support vector regression coupled with wavelet decomposition for drought forecasting in the western area of the DPRK

Published:2022-12-23 Issue: Volume: Page:
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Ham Yong-Sik,Sonu Kyong-Bok,Paek Un-Sim,Om Kum-Chol,Jong Sang-Il,Jo Kum-Ryong

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-022-05781-2.pdf

Reference57 articles.

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3. Anshuka A, Ogtrop FF, Vervoort RW (2019) Drought forecasting through statistical models using standardised precipitation index: a systematic review and meta-regression analysis. Nat Hazards. https://doi.org/10.1007/s11069-019-03665-6

4. Belayneh A, Adamowski J (2012) Standard precipitation Index drought forecasting using neural networks, wavelet neural networks, and support vector regression. Appl Comput Intell Soft Comput. https://doi.org/10.1155/2012/794061

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