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- Title
- Occupant behavior prediction model based on energy consumption using machine learning approaches
- Creator
- Mo, Yunjeong
- Date
- 2018
- Collection
- Electronic Theses & Dissertations
- Description
-
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.
- Title
- The integration of quantitative information with an intelligent decision support system for residential energy retrofits
- Creator
- Mo, Yunjeong
- Date
- 2012
- Collection
- Electronic Theses & Dissertations
- Description
-
The purpose of this research is to support the development of an intelligent Decision Support System (DSS) by integrating quantitative information with expert knowledge in order to facilitate effective retrofit decision-making. To achieve this goal, the Energy Retrofit Decision Process Framework is analyzed. Expert system shell software, a retrofit measure cost database, and energy simulation software are needed for developing the DSS; Exsys Corvid, the NREM database and BEopt were chosen for...
Show moreThe purpose of this research is to support the development of an intelligent Decision Support System (DSS) by integrating quantitative information with expert knowledge in order to facilitate effective retrofit decision-making. To achieve this goal, the Energy Retrofit Decision Process Framework is analyzed. Expert system shell software, a retrofit measure cost database, and energy simulation software are needed for developing the DSS; Exsys Corvid, the NREM database and BEopt were chosen for implementing an integration model. This integration model demonstrates the holistic function of a residential energy retrofit system for existing homes, by providing a prioritized list of retrofit measures with cost information, energy simulation and expert advice. The users, such as homeowners and energy auditors, can acquire all of the necessary retrofit information from this unified system without having to explore several separate systems. The integration model plays the role of a prototype for the finalized intelligent decision support system. It implements all of the necessary functions for the finalized DSS, including integration of the database, energy simulation and expert knowledge.
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