<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/10003363" mdate="2015-11-03 00:00:00"> <author>Liang Zhao and Jili Zhang and Chongquan Zhong</author> <title>The Application of Data Mining Technology in Building Energy Consumption Data Analysis</title> <pages>81 - 85</pages> <year>2016</year> <volume>10</volume> <number>1</number> <journal>International Journal of Computer and Information Engineering</journal> <ee>https://publications.waset.org/pdf/10003363</ee> <url>https://publications.waset.org/vol/109</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>Energy consumption data, in particular those involving public buildings, are impacted by many factors the building structure, climateenvironmental 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. </abstract> <index>Open Science Index 109, 2016</index> </article>