Art

J-GLOBAL ID：201802232656584861   Reference number：18A1690021

Predictive artificial neural network models to forecast the seasonal hourly electricity consumption for a University Campus

大学キャンパスのための季節的時間毎電力消費を予測するための予測人工神経回路網モデル【JST・京大機械翻訳】

Author (5)： Yuan Jihui (Dept. of Architectural Engineering, Graduate School of Engineering, Osaka University, Suita 565-0871, Japan) ,  Yuan Jihui (Dept. of Housing and Environmental Design, Graduate School of Human Life Science, Osaka City University, Osaka 558-8585, Japan) ,  Farnham Craig (Dept. of Housing and Environmental Design, Graduate School of Human Life Science, Osaka City University, Osaka 558-8585, Japan) ,  Azuma Chikako (Dept. of Housing and Environmental Design, Graduate School of Human Life Science, Osaka City University, Osaka 558-8585, Japan) ,  Emura Kazuo (Dept. of Housing and Environmental Design, Graduate School of Human Life Science, Osaka City University, Osaka 558-8585, Japan)
Material： Sustainable Cities and Society
Volume： 42  Page： 82-92  Publication year： 2018 
JST Material Number： W2908A  ISSN： 2210-6707  Document type： Article
Article type： 原著論文  Country of issue： Netherlands (NLD)  Language： ENGLISH (EN)

Abstract/Point： This paper proposes artificial...

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Thesaurus term： feedforward ,  Japan ,  correlation coefficient ,  *electric power consumption ,  *forecast ,  neural network (biomodel) ,  global solar radiation ,  prediction accuracy ,  Human Activities ,  indoor ,  error of mean square ,  back propagation algorithm ,  dry bulb temperature ,  *neural network model ,  *university campus

Author keywords (4)： University Campus ,  Artificial neural network ,  Hourly electricity consumption forecast ,  Root mean square error

JST classification (3)： Solar photovoltaic generation  (NB03090G) ,  Radiation,atmospheric optics  (DC05080C) ,  Solar energy  (LB03030Q)

Terms in the title (6)： 大学キャンパス ,  季節 ,  電力消費 ,  予測 ,  人工 ,  神経回路網モデル