A simple approach for short-term wind speed interval prediction based on independently recurrent neural networks and error probability distribution-Reference-Cited by-同舟云学术

A simple approach for short-term wind speed interval prediction based on independently recurrent neural networks and error probability distribution

Published:2022-01 Issue: Volume:238 Page:122012
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Saeed Adnan^ORCID,Li Chaoshun^ORCID,Gan Zhenhao^ORCID,Xie Yuying,Liu Fangjie

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Bureau of Science and Technology of Zhoushan

Wuhan Science and Technology Bureau Applied Fundamental Research of Wuhan

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference63 articles.

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3. Khodayar M, Wang J. Spatio-temporal graph deep neural network for short-term wind speed forecasting. IEEE Trans Sustain Energy, https://doi.org/10.1109/TSTE.2018.2844102.

4. Tian Z, Li H, Li F. A combination forecasting model of wind speed based on decomposition. Energy, https://doi.org/10.1016/j.egyr.2021.02.002.

5. K.U.Jaseena, Binsu C.Kovoor. Decomposition-based hybrid wind speed forecasting model using deep bidirectional LSTM networks. Energy Convers Manag, https://doi.org/10.1016/j.enconman.2021.113944.

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