Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression-Reference-Cited by-同舟云学术

Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression

Published:2019-12 Issue: Volume:143 Page:842-854
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Liu Hui,Mi Xiwei^ORCID,Li Yanfei,Duan Zhu,Xu Yinan

Funder

National Natural Science Foundation of China, China

Changsha Science & Technology Project

Central South University, China

Central South University

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference44 articles.

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2. Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China;Wang;Renew. Energy,2015

3. Wind speed prediction model using singular spectrum analysis, empirical mode decomposition and convolutional support vector machine;Mi;Energy Convers. Manag.,2019

4. A hybrid wind speed forecasting model based on phase space reconstruction theory and Markov model: a case study of wind farms in northwest China;Wang;Energy,2015

5. Wind power day-ahead prediction with cluster analysis of NWP;Dong;Renew. Sustain. Energy Rev.,2016

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