Z
Zhun (Jerry) Yu
Researcher at Hunan University
Publications - 50
Citations - 2261
Zhun (Jerry) Yu is an academic researcher from Hunan University. The author has contributed to research in topics: Heat exchanger & Phase-change material. The author has an hindex of 16, co-authored 46 publications receiving 1750 citations. Previous affiliations of Zhun (Jerry) Yu include North China Electric Power University & Hong Kong Polytechnic University.
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A systematic procedure to study the influence of occupant behavior on building energy consumption
TL;DR: In this article, a new methodology for examining the influences of occupant behavior on building energy consumption is proposed based on a basic data mining technique (cluster analysis), where min-max normalization is performed as a data preprocessing step before clustering.
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A decision tree method for building energy demand modeling
TL;DR: The results demonstrate that the use of decision tree method can classify and predict building energy demand levels accurately, identify and rank significant factors of building EUI automatically, and provide the combination of significant factors as well as the threshold values that will lead to high building energy performance.
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A review on macro-encapsulated phase change material for building envelope applications
Zhengxuan Liu,Zhun (Jerry) Yu,Tingting Yang,Qin Di,S. Samuel Li,Guoqiang Zhang,Fariborz Haghighat,Mahmood Mastani Joybari +7 more
TL;DR: A comprehensive overview of macro-encapsulated PCM and its integration into building envelopes is provided and a number of important issues have seldom been addressed such as material selection and PCM melting processes at a component level, and optimal locations at a system level.
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A novel methodology for knowledge discovery through mining associations between building operational data
TL;DR: In this paper, a new methodology for examining all associations and correlations between building operational data, thereby discovering useful knowledge about energy conservation is presented, which is based on a basic data mining technique (association rule mining).
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A methodology for identifying and improving occupant behavior in residential buildings
TL;DR: In this paper, the authors developed a methodology for identifying and improving occupant behavior in existing residential buildings, which is based on three basic data mining techniques: cluster analysis, classification analysis, and association rules mining.