基于BP神经网络的城市住宅地价水平模型研究——以杭州市为例

Study of Urban Residential Land Price Level Based on BP Neural Network:Taking Hangzhou as an Example

在揭示城市住宅用地特征的基础上,分析并确定影响住宅用地地价水平的相关因素,并利用BP神经网络构建城市住宅用地地价水平预测模型。通过对杭州市历年住宅用地地价水平预测的个案研究,表明此方法经济、便捷、适应能力强,值得应用与推广的同时,也为加强城市土地价格管理提供科学参考与依据。

On the basis of describing the characteristics of urban residential land, the article analyzes and identifies the relevant factors of residential land price level, and builds the prediction model based on BP neural network. Through the case study of predicting the residential land price level over the years in Han- gzhou city, the paper illustrates this method is economical, convenient, adaptable and feasible. At the same time, it also provides a scientific reference for the urban land price management.