Behavioral Profiles for Building Energy Performance Using eXclusive SOM
Abstract
The identification of user and usage profiles in the built environment is of vital importance both for energy performance analysis and smart control purposes. Clustering tools are a suitable means as they are able to discover representative patterns from a myriad of collected data. In this work, the methodology of an eXclusive Self-Organizing Map (XSOM) is proposed as an evolution of a Kohonen map with outlier rejection capabilities. As will be shown, XSOM characteristics fit perfectly with the targeted application areas.
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