Analysis of Energy Use Behaviors in Residential Buildings Using Real-World Home Energy Sensors-Reference-Cited by-同舟云学术

Analysis of Energy Use Behaviors in Residential Buildings Using Real-World Home Energy Sensors

Published:2022-05-24 Issue: Volume: Page:
ISSN:
Container-title:Computing in Civil Engineering 2021
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Author:

Mo Yunjeong¹²³¹,Zhao Dong¹²³¹,Kang Taewook¹²³¹,Kim Jonghoon¹²³¹

Affiliation:

1. Dept. of Construction Management, College of Computing, Engineering, and Construction, Univ. of North Florida, Jacksonville, FL.

2. School of Planning, Design, and Construction, Dept. Civil and Environmental Engineering, Michigan State Univ., East Lasing, MI.

3. Korea Institute of Civil Engineering and Building Technology, Goyang-si, Gyeonggi-do, South Korea.

Publisher

American Society of Civil Engineers

Link

http://ascelibrary.org/doi/pdf/10.1061/9780784483893.016

Reference10 articles.

1. Aksanli B. Akyurek A. S. and Rosing T. S. “User behavior modeling for estimating residential energy consumption.” Proc. Smart City 360° Springer 348–361.

2. Modeling energy consumption in residential buildings: A bottom-up analysis based on occupant behavior pattern clustering and stochastic simulation.;Diao L.;Energy and Buildings,2017

3. Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior

4. Mo Y. Zhao D. and Sorce J. “Daily Occupant Behavior Pattern Affecting Energy Use in Residential Buildings.” Proc. Construction Research Congress 2020: Computer Applications American Society of Civil Engineers Reston VA 518–526.

5. Mo Y. Zhao D. and Syal M. (2019). “Effective Features to Predict Residential Energy Consumption Using Machine Learning.” Computing in Civil Engineering 2019: Smart Cities Sustainability and Resilience American Society of Civil Engineers Reston VA 284–291.