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dc.contributor.authorJamie Russell
dc.contributor.authorJoseph Cazier
dc.contributor.authorEdgar Hassler
dc.contributor.authorThomas Mueller
dc.date.accessioned2022-01-30T19:51:53Z
dc.date.available2022-01-30T19:51:53Z
dc.date.issued2020
dc.identifier.other%28ASCE%29AE.1943-5568.0000384.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4266106
dc.description.abstractBuildings are complex systems whose energy consumption depends on the interplay of multiple physical and human factors. This paper explored the performance of single-family detached dwellings using the tools of data analytics. The goals of this work were to understand and eventually to predict electrical energy consumption in order to develop strategies to reduce both peak power consumption and annual energy consumption in the residential building sector. Results showed that the year in which a dwelling was built combined with primary heating source is a significant predictor of electricity use.
dc.publisherASCE
dc.titleUsing Data Analytics to Understand Electrical Consumption Patterns of Residential Buildings
dc.typeJournal Paper
dc.journal.volume26
dc.journal.issue1
dc.journal.titleJournal of Architectural Engineering
dc.identifier.doi10.1061/(ASCE)AE.1943-5568.0000384
dc.page04019032
dc.treeJournal of Architectural Engineering:;2020:;Volume ( 026 ):;issue: 001
dc.contenttypeFulltext


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