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J-GLOBAL ID：202102263897443330   Reference number：21A1009857

A Novel Prediction Approach for Short-Term Renewable Energy Consumption in China Based on Improved Gaussian Process Regression

改良Gaussプロセス回帰に基づく中国における短期再生可能エネルギー消費のための新しい予測アプローチ【JST・京大機械翻訳】

Author (5)： Huang Yuansheng (School of Economics and Management, North China Electric Power University, Beijing 102206, China) ,  Yang Lei (School of Economics and Management, North China Electric Power University, Beijing 102206, China) ,  Gao Chong (School of Economics and Management, North China Electric Power University, Baoding 071003, China) ,  Jiang Yuqing (School of Economics and Management, North China Electric Power University, Baoding 071003, China) ,  Dong Yulin (School of Economics and Management, North China Electric Power University, Baoding 071003, China)
Material： Energies (Web)
Volume： 12  Issue： 21  Page： 4181  Publication year： 2019 
JST Material Number： U7016A  ISSN： 1996-1073  CODEN： ENERGA  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Energy consumption issues are ...

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Thesaurus term： algorithm ,  optimization ,  sun ,  geothermy ,  *Gaussian process ,  volatility ,  fossil fuel ,  energy consumption ,  biomass ,  wind force ,  effectiveness ,  prediction model
Semi thesaurus term： 循環型社会 ,  再生可能エネルギー源 ,  エネルギー産業 , 【Automatic Indexing@JST】

Author keywords (5)： renewable energy consumption ,  Gaussian processes regression ,  state transition algorithm ,  five-year project ,  forecasting

JST classification (1)： Energy consumption and energy saving  (LD01000B)

Reference (46)：

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Terms in the title (6)： Gaussプロセス ,  中国 ,  短期 ,  再生可能エネルギー ,  消費 ,  予測