Title: Energy consumption parameter detection of green energy saving building based on artificial fish swarm algorithm
Authors: Lijun Yin; Haoran Yin
Addresses: Xinxiang Vocational and Technical College, Xinxiang 453006, Henan, China ' Yurun holdings Group, Nanjing 210019, Jiangsu, China
Abstract: In order to overcome the low-detection accuracy of traditional methods, an artificial fish swarm algorithm was proposed to detect the energy consumption parameters of green and energy-saving buildings. The type of energy consumption equipment in green and energy-saving buildings is analysed, and the electricity consumption of building energy consumption equipment is taken as the building energy consumption parameter. The hierarchical clustering method was used to establish the classification model of energy consumption parameters, and the energy consumption parameters were classified and processed, and the energy consumption parameters detection model was built, and the preliminary detection results of energy consumption parameters were obtained. The artificial fish swarm algorithm was used to construct the optimisation function of building parameter detection results to obtain the optimal detection results of energy consumption parameters. Experimental results show that the accuracy of the proposed method is between 92.76% and 98.75%, and the practical application effect is good.
Keywords: artificial fish swarm algorithm; green energy saving building; energy consumption parameters; hierarchical clustering.
International Journal of Global Energy Issues, 2022 Vol.44 No.5/6, pp.498 - 510
Received: 17 Mar 2021
Accepted: 19 Jun 2021
Published online: 08 Sep 2022 *