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A Framework For Augmenting Building Performance Models Using Machine Learning And Immersive Virtual Environment, Chanachok Chokwitthaya

LSU Doctoral Dissertations

Building performance models (BPMs), such as building energy simulation models, have been widely used in building design. Existing BPMs are mainly derived using data from existing buildings. They may not be able to effectively address human-building interactions and lack the capability to address specific contextual factors in buildings under design. The lack of such capability often contributes to the existence of building performance discrepancies, i.e., differences between predicted performance during design and the actual performance.

To improve the prediction accuracy of existing BPMs, a computational framework is developed in this dissertation. It combines an existing BPM with context-aware design-specific …