Data mining cubes for buildings, a generic framework for multidimensional analytics of building performance data

Data mining cubes for buildings, a generic framework for multidimensional analytics of building performance data

10.1016/j.enbuild.2021.111195

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Bibliographic Details
Main Authors:	Leprince, Julien, Miller, Clayton, Zeiler, Wim
Other Authors:	THE BUILT ENVIRONMENT
Format:	Article
Language:	English
Published:	ELSEVIER SCIENCE SA 2022
Subjects:	Science & Technology Technology Construction & Building Technology Energy & Fuels Engineering, Civil Engineering Data mining Data cube Generic method Multidimensional analytics Machine learning Building data MISSING VALUES KNOWLEDGE DISCOVERY FAULT-DETECTION ENERGY DEMAND DATA-DRIVEN ELECTRICITY CONSUMPTION OUTLIER DETECTION IMPUTATION CLASSIFICATION DIAGNOSTICS
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/229342
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Institution:	National University of Singapore
Language:	English

Description
Summary:	10.1016/j.enbuild.2021.111195