CINXE.COM
TY - JFULL AU - Liang Zhao and Jili Zhang and Chongquan Zhong PY - 2016/2/ TI - The Application of Data Mining Technology in Building Energy Consumption Data Analysis T2 - International Journal of Computer and Information Engineering SP - 80 EP - 85 VL - 10 SN - 1307-6892 UR - https://publications.waset.org/pdf/10003363 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 109, 2016 N2 - Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given. ER -