| contributor author | Jamie Russell | |
| contributor author | Joseph Cazier | |
| contributor author | Edgar Hassler | |
| contributor author | Thomas Mueller | |
| date accessioned | 2022-01-30T19:51:53Z | |
| date available | 2022-01-30T19:51:53Z | |
| date issued | 2020 | |
| identifier other | %28ASCE%29AE.1943-5568.0000384.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4266106 | |
| description abstract | Buildings 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. | |
| publisher | ASCE | |
| title | Using Data Analytics to Understand Electrical Consumption Patterns of Residential Buildings | |
| type | Journal Paper | |
| journal volume | 26 | |
| journal issue | 1 | |
| journal title | Journal of Architectural Engineering | |
| identifier doi | 10.1061/(ASCE)AE.1943-5568.0000384 | |
| page | 04019032 | |
| tree | Journal of Architectural Engineering:;2020:;Volume ( 026 ):;issue: 001 | |
| contenttype | Fulltext | |