Occupant behavior prediction model based on energy consumption using machine learning approaches
This research will have an impact on residential occupant behavior by helping occupants better understand their own behaviors' effects on energy usage, and detect what changes would improve energy efficiency in their homes. The findings will be beneficial to energy-related industintegrated with research in other fields.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- In Copyright
- Material Type
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Theses
- Authors
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Mo, Yunjeong
- Thesis Advisors
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Zhao, Dong
- Committee Members
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Syal, Matt
Kim, Suk-Kyung
Zhou, Jiayu
- Date
- 2018
- Subjects
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Dwellings--Energy consumption
Consumer behavior--Forecasting
Construction industry
Energy consumption
Technological innovations
United States
- Program of Study
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Planning, Design and Construction - Doctor of Philosophy
- Degree Level
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Doctoral
- Language
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English
- Pages
- xiv, 238 pages
- ISBN
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9780438733367
0438733363
- Permalink
- https://doi.org/doi:10.25335/b9wy-q945