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	Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization
	Peng Wang; Sungmin Yoon; Jiaqiang Wang; Yuebin Yu
刊名	Energy and Buildings
	2019
关键词	Sensor network Virtual in-situ calibration Sensitivity coefficient optimization Reviving calibration Bayesian MCMC Genetic algorithm
ISSN号	0378-7788
URL标识	查看原文
公开日期	[db:dc_date_available]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4608703
专题	湖南大学
作者单位	1.b Durham School of Architectural Engineering & Construction, University of Nebraska-Lincoln, Omaha, United States a School of Civil Engineering, Dalian University of Technology, Dalian City, China 2.College of Civil Engineering, Hunan University, Changsha, Hunan City, China 3.Institute of Urban Science, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon, 22012, Republic of Korea 4.Division of Architecture and Urban Design, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon, 22012, Republic of Korea
推荐引用方式 GB/T 7714	Peng Wang,Sungmin Yoon,Jiaqiang Wang,et al. Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization[J]. Energy and Buildings,2019.
APA	Peng Wang,Sungmin Yoon,Jiaqiang Wang,&Yuebin Yu.(2019).Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization.Energy and Buildings.
MLA	Peng Wang,et al."Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization".Energy and Buildings (2019).

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