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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Vázquez, F.I., Gaceo, S.C., Kastner, W., Morales, J.A.M. (2011). Behavioral Profiles for Building Energy Performance Using eXclusive SOM. In: Iliadis, L., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN AIAI 2011 2011. IFIP Advances in Information and Communication Technology, vol 363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23957-1_4
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DOI: https://doi.org/10.1007/978-3-642-23957-1_4
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