Improved hybrid sparrow search algorithm for an extreme learning machine neural network for short‐term photovoltaic power prediction in 5G energy‐routing base stations-Reference-Cited by-同舟云学术

Improved hybrid sparrow search algorithm for an extreme learning machine neural network for short‐term photovoltaic power prediction in 5G energy‐routing base stations

Published:2022-09-26 Issue:2 Volume:17 Page:336-348
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Gen

Author:

Yan Ming¹²^ORCID,Guo Wenhao³²,Hu Yongle⁴,Xu Feng⁵,Chen Junjiang³²,Du Qi¹²,Zheng Hanbo¹,Qin Tuanfa³²^ORCID

Affiliation:

1. School of Electrical Engineering Guangxi University Xixiangtang NanningGuangxi530004 People's Republic of China

2. Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Xixiangtang NanningGuangxi530004 People's Republic of China

3. School of Computer and Electronic Information Guangxi University Xixiangtang NanningGuangxi530004 People's Republic of China

4. Runjian Co., Ltd Xixiangtang NanningGuangxi530004 People's Republic of China

5. China Unicom Guangxi Branch China Unicom Qingxiu Nanning Guangxi 530007 People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/rpg2.12600

Reference33 articles.