Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking

10.1016/j.apenergy.2020.114920

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Main Authors: ZHAN SICHENG, Liu, Zhaoru, CHONG ZHUN MIN,ADRIAN, Yan, Da
Other Authors: DEPT OF BUILDING
Format: Article
Language:English
Published: ELSEVIER SCI LTD 2021
Subjects:
Online Access:https://scholarbank.nus.edu.sg/handle/10635/191894
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Institution: National University of Singapore
Language: English
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spelling sg-nus-scholar.10635-1918942023-08-29T22:17:19Z Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking ZHAN SICHENG Liu, Zhaoru CHONG ZHUN MIN,ADRIAN Yan, Da DEPT OF BUILDING Science & Technology Technology Energy & Fuels Engineering, Chemical Engineering Building energy benchmarking Smart meter Clustering Building operation Energy conservation BAYESIAN CALIBRATION PATTERN-RECOGNITION TIME-SERIES PERFORMANCE CLASSIFICATION IDENTIFICATION FRAMEWORK PROFILES PREDICTION EFFICIENCY 10.1016/j.apenergy.2020.114920 APPLIED ENERGY 269 2021-06-09T01:13:14Z 2021-06-09T01:13:14Z 2020-07-01 2021-06-08T07:50:30Z Article ZHAN SICHENG, Liu, Zhaoru, CHONG ZHUN MIN,ADRIAN, Yan, Da (2020-07-01). Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking. APPLIED ENERGY 269. ScholarBank@NUS Repository. https://doi.org/10.1016/j.apenergy.2020.114920 0306-2619 1872-9118 https://scholarbank.nus.edu.sg/handle/10635/191894 en ELSEVIER SCI LTD Elements
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
language English
topic Science & Technology
Technology
Energy & Fuels
Engineering, Chemical
Engineering
Building energy benchmarking
Smart meter
Clustering
Building operation
Energy conservation
BAYESIAN CALIBRATION
PATTERN-RECOGNITION
TIME-SERIES
PERFORMANCE
CLASSIFICATION
IDENTIFICATION
FRAMEWORK
PROFILES
PREDICTION
EFFICIENCY
spellingShingle Science & Technology
Technology
Energy & Fuels
Engineering, Chemical
Engineering
Building energy benchmarking
Smart meter
Clustering
Building operation
Energy conservation
BAYESIAN CALIBRATION
PATTERN-RECOGNITION
TIME-SERIES
PERFORMANCE
CLASSIFICATION
IDENTIFICATION
FRAMEWORK
PROFILES
PREDICTION
EFFICIENCY
ZHAN SICHENG
Liu, Zhaoru
CHONG ZHUN MIN,ADRIAN
Yan, Da
Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
description 10.1016/j.apenergy.2020.114920
author2 DEPT OF BUILDING
author_facet DEPT OF BUILDING
ZHAN SICHENG
Liu, Zhaoru
CHONG ZHUN MIN,ADRIAN
Yan, Da
format Article
author ZHAN SICHENG
Liu, Zhaoru
CHONG ZHUN MIN,ADRIAN
Yan, Da
author_sort ZHAN SICHENG
title Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
title_short Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
title_full Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
title_fullStr Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
title_full_unstemmed Building categorization revisited: A clustering-based approach to using smart meter data for building energy benchmarking
title_sort building categorization revisited: a clustering-based approach to using smart meter data for building energy benchmarking
publisher ELSEVIER SCI LTD
publishDate 2021
url https://scholarbank.nus.edu.sg/handle/10635/191894
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