| 注册
首页|期刊导航|中国电机工程学会电力与能源系统学报(英文版)|Ultra-short Term Wind Speed Prediction Using Mathematical Morphology Decomposition and Long Short-term Memory

Ultra-short Term Wind Speed Prediction Using Mathematical Morphology Decomposition and Long Short-term Memory

Mengshi Li Zhiyuan Zhang Tianyao Ji Q.H.Wu

中国电机工程学会电力与能源系统学报(英文版)2020,Vol.6Issue(4):890-900,11.
中国电机工程学会电力与能源系统学报(英文版)2020,Vol.6Issue(4):890-900,11.DOI:10.17775/CSEEJPES.2019.02070

Ultra-short Term Wind Speed Prediction Using Mathematical Morphology Decomposition and Long Short-term Memory

Ultra-short Term Wind Speed Prediction Using Mathematical Morphology Decomposition and Long Short-term Memory

Mengshi Li 1Zhiyuan Zhang 1Tianyao Ji 1Q.H.Wu1

作者信息

  • 1. School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China
  • 折叠

摘要

关键词

Deep learning/long short-term memory network/mathematical morphology/wind speed forecast

Key words

Deep learning/long short-term memory network/mathematical morphology/wind speed forecast

引用本文复制引用

Mengshi Li,Zhiyuan Zhang,Tianyao Ji,Q.H.Wu..Ultra-short Term Wind Speed Prediction Using Mathematical Morphology Decomposition and Long Short-term Memory[J].中国电机工程学会电力与能源系统学报(英文版),2020,6(4):890-900,11.

基金项目

This work was supported by Fundamental Research Funds for Central Universities,(No.2019MS014),and Natural Science Foundation of Guangdong Province (No.2018A030313822). (No.2019MS014)

中国电机工程学会电力与能源系统学报(英文版)

OACSCDCSTPCDEISCI

2096-0042

访问量0
|
下载量0
段落导航相关论文