Abstract
Human living could become very difficult due to a lack of energy. The household sector plays a significant role in energy consumption. Trying to optimize and achieve efficient energy consumption can lead to large-scale energy savings. The aim of this paper is to identify the equipment and property affecting energy efficiency and consumption in residential homes. For this purpose, a hybrid data-mining approach based on K-means algorithms and decision trees is presented. To analyze the approach, data is modeled once using the approach and then without it. A data set of residential homes of England and Wales is arranged in low, medium and high consumption clusters. The C5.0 algorithm is run on each cluster to extract factors affecting energy efficiency. The comparison of the modeling results, and also their accuracy, prove that the approach employed has the ability to extract the findings with greater accuracy and detail than in other cases. The installation of boilers, using cavity walls, and installing insulation could improve energy efficiency. Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results.
Highlights
In today’s world, supplying energy is done through various carriers such as oil and gas, electricity and renewable energy
Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results
The SPSS Modeler of IMB [44] has been implemented with various tools and algorithms based on the CRISP-DM, The Clementine 12.0 released in Jan 2008 and IBM SPSS Modeler 18.0 released in March 2016 [45], software of IBM has been used to perform the data mining process
Summary
In today’s world, supplying energy is done through various carriers such as oil and gas (and products derived from them), electricity and renewable energy. Given the limited resources of energy and the population growth, the increasing annual consumption of energy affects life, the economy, the environment, politics, and so on. Managing energy is a complicated task and has become an important issue in the modern world. The home section has the largest share of energy consumption in most countries. As each house has its own behavior, energy consumption patterns rely on several factors. Decision making concerning the domestic sector’s energy management and efficiency requires taking advantage of modern science capabilities to manage energy efficiency and consumption
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