Research on Influencing Factors of Residential House Using Improved Genetic Algorithm Model and BP neural Network Model

doi:10.1109/ICCASIT53235.2021.9633656

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	Research on Influencing Factors of Residential House Using Improved Genetic Algorithm Model and BP neural Network Model
	Hengxin, Ju 1; Shipeng, Wang 2; Xiaohan, Wu 3
	2021
会议名称	3rd IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021
会议录名称	Proceedings of 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2021
页码	693-697
会议日期	October 20, 2021 - October 22, 2021
会议地点	Changsha, China
出版者	Institute of Electrical and Electronics Engineers Inc.
摘要	Real estate has been an important part of the Chinese economy. It is of great significance to study the factors influencing commercial, residential housing prices for stabilizing economic growth. In this paper, we designed a new index set according to the principle of economics. On this basis, we proposed a Back Propagation neural network model based on genetic algorithm optimization. The experimental results show that the improved BP neural network based on Genetic Algorithm has a better fitting effect than the traditional fitting model and BP neural network model, and MSE decreases by 35.6% and 14.5%, respectively. Through the improved model, we can reference the study of housing prices, real estate buyers, and investors' decision-making. © 2021 IEEE
关键词	Economic analysis Housing Genetic algorithms Costs Investments Decision making Algorithm model BP neural networks model Chinese economy GA model Housing prices Influencing factor Nonlinear fitting Optimisations Real-estates Residential house
DOI	10.1109/ICCASIT53235.2021.9633656
收录类别	EI
语种	英语
EI入藏号	20220511566095
EI主题词	Neural network models
EI分类号	403.1 Urban Planning and Development ; 723.4 Artificial Intelligence ; 911 Cost and Value Engineering ; Industrial Economics ; 911.2 Industrial Economics ; 912.2 Management
原始文献类型	Conference article (CA)
文献类型	会议论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/33419
专题	兰州财经大学
作者单位	1.School of Economic Management, Lanzhou University of Technology, Gansu, Lanzhou; 730050, China; 2.Longqiao College of Lanzhou University of Finance and Economics, Gansu, Lanzhou; 730101, China; 3.Division of Business and Management (DBM), BNU-HKBU United International College (UIC), Zhuhai, China
推荐引用方式 GB/T 7714	Hengxin, Ju,Shipeng, Wang,Xiaohan, Wu. Research on Influencing Factors of Residential House Using Improved Genetic Algorithm Model and BP neural Network Model[C]:Institute of Electrical and Electronics Engineers Inc.,2021:693-697.