Study On The Price Evaluation Of Secondhand Residential Buildings In Beijing Based On Neural Network

China's reform and opening up has been methodically carried out for the 40 th anniversary,during this period,the domestic economy has been rapid development,at the same time,the real estate industry with the deepening of reform and opening up and rapid economic development and continuous prosperity forward.In recent years,the real estate industry has witnessed frequent transactions of second-hand residential houses,which has increased the market demand for real estate price assessment.The effective evaluation of second-hand housing price not only concerns the legal protection of citizens' rights and interests of fair transaction,but also concerns the healthy operation of China's real estate market.At present,the domestic evaluation of second-hand housing is still in the primary stage,mostly depending on the personal experience of real estate price appraisers,but this subjective evaluation mechanism is lack of certain evaluation basis,easy to bring about large housing price error.Based on this,This thesis adopts the method of modeling to conduct quantitative evaluation of second-hand housing prices,in order to provide a new idea for the establishment of a more scientific and rigorous second-hand housing price evaluation system.This thesis first to the Beijing real estate market to analyze the development situation of this year,corresponding to the selection of housing price evaluation indicators and evaluation system is established,and in Beijing from 2017 to 2018,the second-hand house transaction data acquisition,draw lessons from foreign advanced real estate price evaluation theory,price theory,from the perspective of consumer demand for residential characteristics understand prices,using R Studio software based on back propagation neural network model of second-hand housing prices evaluation algorithm,through inspection of back propagation neural network model and the traditional multiple linear regression model to empirical analysis,The results show that the back-propagation neural network algorithm has high accuracy and certain effectiveness in real estate price evaluation,and can be further promoted and applied.