Meta-learning strategy based on user preferences and a machine recommendation system for real-time cooling load and COP forecasting

•A new meta-learning recommendation system is proposed.•The new system concerned two-stage (subjective and objective) user preferences.•Multi-objective decision making algorithms (MODMA) are used in option optimization.•A new “walking slide method” aimed at some extremely special cases is proposed.•...

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Vydané v:	Applied energy Ročník 270; s. 115144
Hlavní autori:	Li, Wenqiang, Gong, Guangcai, Fan, Houhua, Peng, Pei, Chun, Liang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 15.07.2020
Predmet:	algorithms Artificial neural network (ANN) buildings cooling Cooling load prediction data collection energy energy conservation Meta-learning monitoring neural networks prediction Recommendation system User preferences Artificial neural network (ANN) User preferences Cooling load prediction Meta-learning Recommendation system
ISSN:	0306-2619, 1872-9118
On-line prístup:	Získať plný text
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