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Research On Prediction Of Subwaylines Housing Transaction Price On BP Neural Network

Posted on:2022-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:R XuFull Text:PDF
GTID:2518306542450234Subject:Project management
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In the past decades,China's real estate is not only a pillar industry of the economy,but also a hot issue of people' s livelihood.The future trend of housing prices has triggered thinking and hot discussion among residents and scholars.Metro transportation is in the urbanization process today,greatly alleviating the pressure of public transportation.In such an environment,the subway and real estate two seemingly unrelated market single products are virtually linked together.When the house has a subway around the traffic,which can have more convenient transportation and commerce,so the houses along the subway can enjoy a lot of potential benefits,and the housing price will,to some extent,be higher than the houses without the subwayThe theory of gray correlation,selected the factors affecting the housing price,and analyzed the selected factors with the highest influence as the final housing price predictor.This paper is based on the optimization of genetic algorithm to discuss the price of property prediction.Based on the perspective of ordinary home buyers,and for the government to play a certain theoretical reference in the future housing price regulation,through the establishment of an improved BP neural network model to predict the existing housing price.The results are as follows:1)In the process of data selection used in this article,20 predictors were selected by combing literature and reference buyer willingness;using gray correlation,three predictors were less than 0.6,and 17 factors affecting the housing price;2)Contrare the fitting curve of standard BP neural network and the prediction of BP neural network model,and the BP neural network model is selected as the prediction model of this paper;3)Through example analysis,400 groups around Metro Line 1 were collected as the training set and 100 groups and effectiveness of the prediction of 20 communities:unplanned-construction-operation in the next five years.The results show that the housing price along the local railway will be higher than the surrounding metro state.By establishing the improved BP neural network based on genetic algorithm,it can accurately predict the housing price of the surrounding houses with planned subway under appropriate conditions and provide relevant reference basis for buyers.
Keywords/Search Tags:Urumqi Metro, housing price prediction, BP neural network, genetic algorithm, correlation analysis
PDF Full Text Request
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