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Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method
Li, Chengdong1; Zhang, Guiqing1; Wang, Ming1; Yi, Jianqiang2
Source PublicationSOFT COMPUTING
2013-11-01
Volume17Issue:11Pages:2075-2088
SubtypeArticle
AbstractIn the research domain of intelligent buildings and smart home, modeling and optimization of the thermal comfort and energy consumption are important issues. This paper presents a type-2 fuzzy method based data-driven strategy for the modeling and optimization of thermal comfort words and energy consumption. First, we propose a methodology to convert the interval survey data on thermal comfort words to the interval type-2 fuzzy sets (IT2 FSs) which can reflect the inter-personal and intra-personal uncertainties contained in the intervals. This data-driven strategy includes three steps: survey data collection and pre-processing, ambiguity-preserved conversion of the survey intervals to their representative type-1 fuzzy sets (T1 FSs), IT2 FS modeling. Then, using the IT2 FS models of thermal comfort words as antecedent parts, an evolving type-2 fuzzy model is constructed to reflect the online observed energy consumption data. Finally, a multiobjective optimization model is presented to recommend a reasonable temperature range that can give comfortable feeling while reducing energy consumption. The proposed method can be used to realize comfortable but energy-saving environment in smart home or intelligent buildings.
KeywordType-2 Fuzzy Data-driven Method Thermal Comfort Multiobjective Optimization Energy Saving
WOS HeadingsScience & Technology ; Technology
WOS KeywordINTERVAL TYPE-2 ; SYSTEMS ; SETS ; FUZZISTICS ; IDENTIFICATION ; APPROXIMATION ; STABILIZATION ; CONTROLLERS ; PREDICTION ; NUMBER
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000325822900010
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4168
Collection综合信息系统研究中心
Corresponding AuthorLi, Chengdong
Affiliation1.Shandong Jianzhu Univ, Sch Informat & Elect Engn, Jinan, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Li, Chengdong,Zhang, Guiqing,Wang, Ming,et al. Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method[J]. SOFT COMPUTING,2013,17(11):2075-2088.
APA Li, Chengdong,Zhang, Guiqing,Wang, Ming,&Yi, Jianqiang.(2013).Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method.SOFT COMPUTING,17(11),2075-2088.
MLA Li, Chengdong,et al."Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method".SOFT COMPUTING 17.11(2013):2075-2088.
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