A Novel Methodology for Identifying Associations and Correlations Between Household Appliance Behaviour in Residential Buildings. (November 2015)

• Record Type: Journal Article
• Authors: Yu, Z.; Li, J.; Li, H.Q.; Han, J.; Zhang, G.Q.
• Is Part Of: Energy procedia. Volume 78(2015)
• Page Start: 591
• Page End: 596
• Publication Date: 2015-11
• Subjects: Occupant behaviour -- Building energy consumption -- household appliance -- Datamining -- Association rule mining; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2015.11.024
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: This paper reports the development of a new methodology for examining all associations and correlations between various household appliance behaviour, thereby discovering hidden patterns of occupant behaviour in residential buildings. The method is based on a basic data mining technique (association rule mining). Its strength lies in its ability to analyse both continuous and nominal data, and examine all associations and correlations automatically. To demonstrate its applicability, it was applied to the measured end-use electricity data in a selected residential building with comprehensive household appliances in Japan. The results show that both direct and indirect associations between occupant behaviour were discovered. The results obtained could provide a deep insight into the interaction between different behaviour, offer detailed recommendations for reducing building energy consumption, and enable the best input parameters of occupant behaviour prediction models to be identified.