Short-term wind speed forecasts through hybrid model based on improved variational mode decomposition-Reference-Cited by-同舟云学术

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Short-term wind speed forecasts through hybrid model based on improved variational mode decomposition

Published:2024-02-02 Issue:10 Volume:21 Page:2281-2298
ISSN:1543-5075
Container-title:International Journal of Green Energy
language:en
Short-container-title:International Journal of Green Energy

Author:

Yiyan Dai¹,Mingjin Zhang¹²,Xu Xin¹,Xiaohu Chen³,Yongle Li¹,Maoyi Liu⁴

Affiliation:

1. Department of Bridge Engineering, Southwest Jiaotong University, Chengdu, China

2. State Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University, Chengdu, China

3. Department of Bridge Business, T.Y. Lin International Engineering Consulting (Chongqing) Co., Ltd, Chongqing, China

4. Department of Science and Technology, Chongqing Construction Investment(Group) Co., Ltd, Chongqing, Chongqing, China

Funder

National Natural Science Foundation of China

Provincial Science Foundation for Distinguished Youth of Sichuan

Chongqing Science Fund for Distinguished Young Scholars

Chongqing Technological Innovation and Application Development Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15435075.2023.2301399

Reference55 articles.

1. A review on renewable energy and electricity requirement forecasting models for smart grid and buildings

2. Wind speed prediction model using ensemble empirical mode decomposition, least squares support vector machine and long short-term memory

3. Spotted Hyena Optimizer for Solving Engineering Design Problems

4. Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems

5. A short-term wind power prediction model based on CEEMD and WOA-KELM

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