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Behavioral Profiles for Building Energy Performance Using eXclusive SOM

  • Félix Iglesias Vázquez
  • Sergio Cantos Gaceo
  • Wolfgang Kastner
  • José A. Montero Morales
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 363)

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.

Keywords

pattern discovery neural network Self-Organizing Map user behavior and profiling energy performance simulation building automation 

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Copyright information

© International Federation for Information Processing 2011

Authors and Affiliations

  • Félix Iglesias Vázquez
    • 1
  • Sergio Cantos Gaceo
    • 2
  • Wolfgang Kastner
    • 1
  • José A. Montero Morales
    • 2
  1. 1.Automation Systems GroupVienna University of TechnologyViennaAustria
  2. 2.La Salle (Universitat Ramon Llull), Electronics & CommunicationBarcelonaSpain

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