Abstract
The consumption of building energy was increasing every year in the past in China. It is a big problem to be solved about how to make the building energy consumption to be more reasonable. In order to obtain the feature of building energy consumption with its electrical instructions, a decision-tree algorithm is designed to mine the data of energy consumption of electricity. According to the analysis of the attribute quantity factors, comparing the factors classification information gain value, and analysis the proportion of power consumption factors, a typical energy consumption sample of a laboratory in university was modeled and analyzed in this paper. Experimental results show that the seasonal change factor has a great influence on the energy consumption of the building. And according to this conclusion, a suitable energy-efficiency device is planed.
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Acknowledgments
This work is supported by Fujian Science and Technology Department (No. 2014H0008), Fujian Transportation Department (No. 2015Y0008), Fujian Education Department (Nos. JK2014033, JA14209, JA1532), and Fujian University of Technology (Nos. GYZ13125, 61304199, GY-Z160064). Many thanks to the anonymous reviewers, whose insightful comments made this a better paper.
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Pang, Y., Jiang, X., Zou, F., Gan, Z., Wang, J. (2018). Research on Energy Consumption of Building Electricity Based on Decision Tree Algorithm. In: Krömer, P., Alba, E., Pan, JS., Snášel, V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham. https://doi.org/10.1007/978-3-319-68527-4_29
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DOI: https://doi.org/10.1007/978-3-319-68527-4_29
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