Electricity Consumption Forecasting Scheme via Improved LSSVM with Maximum Correntropy Criterion.

Duan, Jiandong; Qiu, Xinyu; Ma, Wentao; Tian, Xuan; Shang, Di

Duan, Jiandong; Qiu, Xinyu; Ma, Wentao; Tian, Xuan; Shang, Di.

Afiliação

Duan J; School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
Qiu X; School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
Ma W; School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
Tian X; School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.
Shang D; School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.

Entropy (Basel) ; 20(2)2018 Feb 08.

Article em En | MEDLINE | ID: mdl-33265203

Palavras-chave

K-fold cross-validation; electricity consumption forecasting; least-square support vector machine; maximum correntropy criterion

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article