Hybrid model based on VMD decomposition, clustering analysis, long short memory network, ensemble learning and error complementation for short-term wind speed forecasting assisted by Flink platform-Reference-Cited by-同舟云学术

Hybrid model based on VMD decomposition, clustering analysis, long short memory network, ensemble learning and error complementation for short-term wind speed forecasting assisted by Flink platform

Published:2022-12 Issue: Volume:261 Page:125248
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Sun Zexian^ORCID,Zhao Mingyu,Zhao Guohong

Publisher

Elsevier BV

Subject

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

Reference30 articles.

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3. A combined forecasting model for time series: application to short-term wind speed forecasting;Liu;Appl Energy,2020

4. Hybrid model for renewable energy and loads prediction based on data mining and variational mode decomposition;Dou;IET Gener, Transm Distrib,2018

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