期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 56, 期 -, 页码 242-255出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2016.03.002
关键词
Energy efficiency; Smart building; Energy efficiency indicators; Analytics; Expert System; Decision support system
类别
资金
- KnoholEM [FP7-285229]
The rapidly growing world energy use already has concerns over the exhaustion of energy resources and heavy environmental impacts. As a result of these concerns, a trend of green and smart cities has been increasing. To respond to this increasing trend of smart cities with buildings every time more complex, in this paper we have proposed a new method to solve energy inefficiencies detection problem in smart buildings. This solution is based on a rule-based system developed through data mining techniques and applying the knowledge of energy efficiency experts. A set of useful energy efficiency indicators is also proposed to detect anomalies. The data mining system is developed through the knowledge extracted by a full set of building sensors. So, the results of this process provide a set of rules that are used as a part of a decision support system for the optimisation of energy consumption and the detection of anomalies in smart buildings. (C) 2016 Elsevier Ltd. All rights reserved.
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