A new decomposition-ensemble strategy fusion with correntropy optimization learning algorithms for short-term wind speed prediction-Reference-Cited by-同舟云学术

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A new decomposition-ensemble strategy fusion with correntropy optimization learning algorithms for short-term wind speed prediction

Published:2024-09 Issue: Volume:369 Page:123589
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Zhao Ning,Su Yi,Dai Xianxing,Jia Shaomin,Wang Xuewei

Funder

Sichuan Agricultural University

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Reference99 articles.

1. Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies;Nezhad;Renew Sust Energ Rev,2022

2. Global wind report 2021;GWEC,2021

3. Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization;Lv;Appl Energy,2022

4. A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series;Karasu;Energy,2020

5. Short-term wind speed prediction using time varying filter-based empirical mode decomposition and group method of data handling-based hybrid model;Jiang;Energy Convers Manag,2020

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