基于BP神经网络的轨道交通对房地产价格影响分析

Research on Impact of Rail Transit on Real Estate Price Based on BP Neural Network Model

基于轨道交通对房地产影响的复杂性和不确定性,运用基于投标租金模型的BP神经网络模型,以北京八通线起点站为中心,选取13组楼盘为样本,以住宅价格为输出层,以汇集时间、行车时间为输入层,采用仅有一个隐含层的3层神经网络进行分析,得出交通成本与住宅价格的神经网络模型.结合样本数据验证了模型的准确性,为人们准确进行房地产收益开发预测提供了一种有效的方法.

Based on the complexity and uncertainty of rail transit＇s effect on real estate and using BP neural network model based on Bid-Rent model, with starting station of Beijing Bating Line as the central point, this paper selects a group of 13 real estate samples to analyze the three-layer neural network with housing prices as the output layer, .the pool time and travel time as the input layer and one hidden layer, and obtains the neural network model of transit costs and house prices. Combined with sample examples, the accuracy of neural network model is verified, which can provide effective method to estimate real estate development proceeds.