SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods

10.1016/j.apenergy.2020.115981

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Bibliographic Details
Main Authors:	Roth, Jonathan, Martin, Amory, Miller, Clayton, Jain, Rishee K
Other Authors:	BUILDING
Format:	Article
Language:	English
Published:	ELSEVIER SCI LTD 2021
Subjects:	Urban building energy model Supervised machine learning Convex optimization Smart meter Energy efficiency Energy prediction
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/189342
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Institution:	National University of Singapore
Language:	English

id	sg-nus-scholar.10635-189342
record_format	dspace
spelling	sg-nus-scholar.10635-1893422024-11-09T02:22:52Z SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods Roth, Jonathan Martin, Amory Miller, Clayton Jain, Rishee K BUILDING Dr Clayton Carl Miller Urban building energy model Supervised machine learning Convex optimization Smart meter Energy efficiency Energy prediction 10.1016/j.apenergy.2020.115981 APPLIED ENERGY 280 2021-04-15T03:23:18Z 2021-04-15T03:23:18Z 2020-12-15 2021-04-15T02:22:49Z Article Roth, Jonathan, Martin, Amory, Miller, Clayton, Jain, Rishee K (2020-12-15). SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods. APPLIED ENERGY 280. ScholarBank@NUS Repository. https://doi.org/10.1016/j.apenergy.2020.115981 03062619 18729118 https://scholarbank.nus.edu.sg/handle/10635/189342 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	Urban building energy model Supervised machine learning Convex optimization Smart meter Energy efficiency Energy prediction
spellingShingle	Urban building energy model Supervised machine learning Convex optimization Smart meter Energy efficiency Energy prediction Roth, Jonathan Martin, Amory Miller, Clayton Jain, Rishee K SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
description	10.1016/j.apenergy.2020.115981
author2	BUILDING
author_facet	BUILDING Roth, Jonathan Martin, Amory Miller, Clayton Jain, Rishee K
format	Article
author	Roth, Jonathan Martin, Amory Miller, Clayton Jain, Rishee K
author_sort	Roth, Jonathan
title	SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
title_short	SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
title_full	SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
title_fullStr	SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
title_full_unstemmed	SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
title_sort	syncity: using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
publisher	ELSEVIER SCI LTD
publishDate	2021
url	https://scholarbank.nus.edu.sg/handle/10635/189342
_version_	1821225578119823360

SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods

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