摘要
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.
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.
