Hongyin Chen, Songcen Wang, Ming Zhong, Lu Jin, Xiaoqiang Jia, Yi Guo, Xinhe Zhang, Wei Huang
{"title":"A comprehensive evaluation method of heat source tower heat pump applicability considering regional climate differences","authors":"Hongyin Chen, Songcen Wang, Ming Zhong, Lu Jin, Xiaoqiang Jia, Yi Guo, Xinhe Zhang, Wei Huang","doi":"10.3233/jcm-226957","DOIUrl":null,"url":null,"abstract":"The heat source tower heat pump system is widely used in large and medium-sized air conditioning systems due to its good energy-saving advantages. However, there is no relatively reasonable evaluation system for the applicability of heat source tower heat pumps due to significant regional climate differences. Therefore, in order to better comprehensively evaluate the applicability of the heat source tower heat pump system, a comprehensive evaluation index system for the applicability of the heat source tower heat pump system was first constructed. On the basis of this evaluation index, an applicability evaluation model based on backpropagation neural network is constructed. In response to the slow convergence speed and susceptibility to local values in the application process of this evaluation model, particle swarm optimization algorithm is used to improve it. A comprehensive evaluation model for the applicability of heat source tower heat pumps based on improved backpropagation neural networks has been constructed. For the evaluation model constructed in the study, experimental data from four different regions were selected for validation. The experimental results show that in the training set, the F-Measure value of the evaluation model reaches 0.949, and in the test set, the F-Measure value of the model reaches 0.973. The comprehensive evaluation data from four regions indicate that the heat source tower heat pump system can achieve different heating and cooling effects in different regions. This indicates that the proposed comprehensive evaluation model for the applicability of heat source tower heat pumps based on this improved method has good evaluation results. It can conduct a good analysis of the applicability of the heat source tower heat pump system, providing effective support for developing reasonable and energy-saving refrigeration and heating methods in different regions.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"120 8","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Methods in Sciences and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/jcm-226957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The heat source tower heat pump system is widely used in large and medium-sized air conditioning systems due to its good energy-saving advantages. However, there is no relatively reasonable evaluation system for the applicability of heat source tower heat pumps due to significant regional climate differences. Therefore, in order to better comprehensively evaluate the applicability of the heat source tower heat pump system, a comprehensive evaluation index system for the applicability of the heat source tower heat pump system was first constructed. On the basis of this evaluation index, an applicability evaluation model based on backpropagation neural network is constructed. In response to the slow convergence speed and susceptibility to local values in the application process of this evaluation model, particle swarm optimization algorithm is used to improve it. A comprehensive evaluation model for the applicability of heat source tower heat pumps based on improved backpropagation neural networks has been constructed. For the evaluation model constructed in the study, experimental data from four different regions were selected for validation. The experimental results show that in the training set, the F-Measure value of the evaluation model reaches 0.949, and in the test set, the F-Measure value of the model reaches 0.973. The comprehensive evaluation data from four regions indicate that the heat source tower heat pump system can achieve different heating and cooling effects in different regions. This indicates that the proposed comprehensive evaluation model for the applicability of heat source tower heat pumps based on this improved method has good evaluation results. It can conduct a good analysis of the applicability of the heat source tower heat pump system, providing effective support for developing reasonable and energy-saving refrigeration and heating methods in different regions.
期刊介绍：
The major goal of the Journal of Computational Methods in Sciences and Engineering (JCMSE) is the publication of new research results on computational methods in sciences and engineering. Common experience had taught us that computational methods originally developed in a given basic science, e.g. physics, can be of paramount importance to other neighboring sciences, e.g. chemistry, as well as to engineering or technology and, in turn, to society as a whole. This undoubtedly beneficial practice of interdisciplinary interactions will be continuously and systematically encouraged by the JCMSE.
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