基于BP神经网络的住宅需求预测研究  

House Demand Prediction Based on BP Neural Network

作　　者：江涛[1] 陈小鸣[1] 

机构地区：[1]武汉理工大学管理学院,湖北武汉430070

出　　处：《武汉理工大学学报（信息与管理工程版）》2006年第9期1-3,共3页Journal of Wuhan University of Technology：Information & Management Engineering

基　　金：国家自然科学基金资助项目(70271033)

摘　　要：影响住宅需求的因素众多、错综复杂,因此住宅需求预测问题是一个非常复杂的非线性问题。分析了住宅需求的影响因素,建立了住宅市场需求的BP神经网络预测模型。根据14组大连市有关统计数据,借助M atlab6.5软件进行预测,结果表明应用BP神经网络对住宅需求进行预测,具有可行性和高效性。Well - predicted house demand is an important pre - condition for improving house market management. Factors that influence house demand are anfractuous. The prediction of house demand is a very complicated nonlinear problem. Factors influencing house demand are analyzed and a prediction model of house demand based on BP neural network is established. Applying 14 groups of statistics of Dalian city to the model and with the help of Matlab6.5,the forecasting result shows that BP neural network is feasible and effective in predicting house demand.

关 键 词：住宅需求 预测模型 神经网络 

分 类 号：F224.9[经济管理—国民经济]