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Zhao, J., Lasternas, B., Lam, K.P., Yun, R. and Loftness, V. (2014) Occupant Behavior and Schedule Modeling for Building Energy Simulation through Office Appliance Power Consumption Data Mining. Energy Build., 82, 341-355. https://doi.org/10.1016/j.enbuild.2014.07.033

has been cited by the following article:

• TITLE: Identification of Patterns of Consumption through the Daily Mean Outdoor Temperature

  AUTHORS: Aparicio-Ruiz Pablo, Guadix-Martín José, Onieva-Giménez Luis, Cortés-Achedad Pablo, Muñuzuri-Sanz Jesús

  KEYWORDS: Pattern Recognition, Identification, Clustering, Energy

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.5 No.3B, August 11, 2017

  ABSTRACT: The identification and recognition of patterns in the context of building is a necessary feedback to create intelligent buildings. In this context, the key is empowering the systems with learning elements to make decisions. The challenge is detected element to predict the human behavior in the building. Daily mean outdoor temperature is one of the variables with incidence in the human comfort due to the weather adaptation of the users. In this paper it analyzed the consumption in an office respect to the internal temperature and the daily mean temperature through cluster techniques. The cluster can be used as a forecasting of consumption.