Title: Green building energy consumption data detection method based on Naive Bayesian algorithm

Authors: Jingchen Shi

Addresses: Department of Architectural Engineering, Xinxiang Vocational and Technical College, Xinxiang, Henan, China

Abstract: In order to overcome the accuracy of energy consumption data acquisition and the low timeliness of the detection process existing in the traditional detection methods, a green building energy consumption data detection method based on Naive Bayes algorithm is designed in this paper. After collecting energy consumption data, cluster processing is carried out. Then, on the basis of the analysis of Bayesian basic principle, the Naive Bayesian classification model was designed based on the fast clustering calculation results, and the green building energy usage was analysed, and the energy consumption data quota index was designed, and the energy consumption data verification was completed by combining the Naive Bayesian classification model. The experimental results show that the building energy consumption load collected by this method is closer to the actual energy consumption load, and the detection process takes less than 3.5 min, which fully demonstrates the effectiveness of this method.

Keywords: Naive Bayes algorithm; building energy consumption data; data detection; energy consumption quota; data clustering.

DOI: 10.1504/IJGEI.2022.10049387

International Journal of Global Energy Issues, 2022 Vol.44 No.5/6, pp.379 - 395

Received: 13 Jan 2021
Accepted: 04 Mar 2021

Published online: 08 Sep 2022 *

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