Analysis Of Influencing Factors Of Hosing Price In Hefei

In 2016,the housing price in Hefei rose by as much as the first in the country,ar ousing widespread concern in the community.Due to the many factors that affect the housing price,housing price itself is a complex non-linear system.How to establish a model with less scientific and reasonable error to predict the housing price trend is a t op priority.On the one hand,this paper analyzes the current situation of housing prices in Hefei and draws the current development trend.On the other hand,the main factors affecting housing prices are established through the establishment of a multivariate logistic regression model;finally,the future BP algorithm is used to predict the future of Hefei City.Housing price trend.Firstly,this paper chooses to analysis the changes of housing price trends in recent years in Hefei City.The time series diagram shows that the housing prices are non-stationary;Secondly,from the regional perspective,by comparing the relevant indicators of each region with the radar map,we can find all areas of Hefei City.There are obvious differences between the housing price and the influencing factors.Third,based on the multiple logarithmic regression model,the factors affecting housing prices in Hefei city are screened,dummy variables are introduced to better analyze the influence of policy factors;finally,the BP is constructed.The model,which uses the weight adjustment formula to increase the momentum term and set the global error to the logarithmic mean minimum error,prevents the neural network from fitting to the minimum and also increases the convergence speed.Through continuous debugging,the hidden neuron is determined to be When ten weight matrices have the smallest change,the fitting error at this time is also the smallest.To sum up,the available results are as follows:First,housing prices have a non-linear development trend over time,and combined with the analysis of literature materials,the turning point at the end of 2016 was caused by changes in real-estate corporations and policies.The relative error of time-series forecast results is as high as 12.988.%,also shows that the housing price is not a simple time series function,but is affected by complex systems related to multiple factors;Second,the analysis of regional factors can get the highest average transaction price and supply price in Hefei Municipal District,but the new increase is At least,there is a clear shortage of supply,while in Feixi County,although the average transaction price is low,it catches up with the transaction area.Third,the factors affecting the housing price in Hefei city mainly include location factors,transaction area,and supply.The price,per capita disposable income,interest rate,and policy factors lead to the fact that although the tightening housing price policy has the ability to delay housing price changes,it still cannot change the rising trend of the overall house price in Hefei;Fourth,the improved BP model for Hefei City Housing prices are forecasted and the values for the four regions in August 2017 are obtained,with relative errors below 5%,with one Reference value.