New PSO-SVM Short-Term Wind Power Forecasting Algorithm Based on the CEEMDAN Model | Zendy

Hong You | Zendy; Shixiong Bai | Zendy; Rui Wang | Zendy; Zhixiong Li | Zendy; Shuchen Xiang | Zendy; Feng Huang | Zendy

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New PSO-SVM Short-Term Wind Power Forecasting Algorithm Based on the CEEMDAN Model

Author(s) -

Hong You,

Shixiong Bai,

Rui Wang,

Zhixiong Li,

Shuchen Xiang,

Feng Huang

Publication year - 2022

Publication title -

journal of electrical and computer engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.318

H-Index - 25

eISSN - 2090-0155

pISSN - 2090-0147

DOI - 10.1155/2022/7161445

Subject(s) - hilbert–huang transform , support vector machine , wind power , wind power forecasting , particle swarm optimization , noise (video) , kernel (algebra) , term (time) , algorithm , mode (computer interface) , electric power system , wind speed , power (physics) , computer science , artificial intelligence , mathematics , engineering , white noise , statistics , meteorology , physics , quantum mechanics , combinatorics , electrical engineering , image (mathematics) , operating system

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