An effective wind speed prediction model combining secondary decomposition and regularised extreme learning machine optimised by cuckoo search algorithm-Reference-Cited by-同舟云学术

An effective wind speed prediction model combining secondary decomposition and regularised extreme learning machine optimised by cuckoo search algorithm

Published:2022-05-05 Issue:8 Volume:25 Page:1406-1433
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Zhang Ye¹^ORCID,Zhang Wenyu¹²,Guo Zhenhai³,Zhang Shuwen¹

Affiliation:

1. College of Atmospheric Sciences Lanzhou University Lanzhou China

2. School of Geoscience and Technology Zhengzhou University Zhengzhou China

3. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2737

Reference45 articles.

1. Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey

2. A novel combined model based on advanced optimization algorithm for short-term wind speed forecasting

3. Energy, exergy and economic analysis of a hybrid renewable energy with hydrogen storage system

4. Active load control of large wind turbines using state-space methods and disturbance accommodating control

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