基于RBF网络的二手房价格评估

Price appraisal of second-hand housing based on RBF networks

为了反映评估过程的非线性,合理确定二手房价格,通过分析传统评估方法的不足,提出了基于径向基函数(RBF)神经网络的二手房价格评估模型.模型包括数据库、输入、筛选、学习、测试、评估、输出、知识库8 个模块.利用该模型对杭州市二手房市场进行了实证分析,网络测试取得了良好的结果,证明了基于RBF网络的二手房价格评估方法的实用性和有效性.

To reflect the nonlinear nature of appraisal process and determine the reasonable price of second-hand housing, a novel price appraisal model of second-hand housing based on radial basis function (RBF) was put forward through analyzing the shortcomings of the traditional appraisal methods. This model was composed of 8 modules, including databank module, input module, selecting module, training module, testing module, appraising module, output module, and knowledge databank module. Hangzhou's second-hand housing market was surveyed by using the proposed model. The good performance of the RBF networks based model proves its practicability and efficiency.