A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings

Renewable and Sustainable Energy Reviews

Volumn 81, Issue , 2018, Pages 1365-1377

  Miller, Clayton ^a   Nagy, Zoltán ^b   Schlueter, Arno ^c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b The University of Texas at Austin   (United States)

^c ETH ZURICH   (Switzerland)

Author keywords

Building controls and optimization; Building performance analysis; Clustering; Data mining; Novelty detection; Portfolio analysis; Review; Smart meter analysis; Unsupervised learning; Visual analytics

Indexed keywords

HOUSING; LEARNING ALGORITHMS; LEARNING SYSTEMS; SMART METERS; UNSUPERVISED LEARNING; VISUALIZATION;

ANALYTIC TECHNIQUE; BUILDING CONTROL AND OPTIMIZATION; BUILDING CONTROLS; BUILDING PERFORMANCE ANALYSIS; CLUSTERINGS; CONTROL AND OPTIMIZATION; NOVELTY DETECTION; PORTFOLIO ANALYSIS; SMART METER ANALYSE; VISUAL ANALYTICS;

DATA MINING;

EID: 85020470195     PISSN: 13640321     EISSN: 18790690     Source Type: Journal    
DOI: 10.1016/j.rser.2017.05.124     Document Type: Review

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