基于BP神经网络的房价预测研究——以邯郸市为例

Forecast of Housing Price Based on BP Neu-ral Network—Taking Handan as an Example

摘要: BP神经网络是截止目前应用最为广泛的一种网络结构模型，其对变量之间的非线性关系有着极强的拟合映射能力。本文以邯郸市2003年至2016年的平均房价以及主要因素数据为对象，采用BP神经网络来构建房价预测模型。实验结果显示，在相对稳定的外部环境下，BP神经网络对邯郸市的房价实现了有效预测。

Abstract: BP neural network is a network structure model, which is the most widely used currently. It has a strong ability to fit and map the nonlinear relationship between variables. This paper takes the average house price and main factor data of Handan from 2003 to 2016 as the object, and uses BP neural network to construct a house price forecasting model. The experimental result shows that BP neural network can effectively predict the housing prices in Handan in a relatively stable ex-ternal environment.