摘要
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.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2005年第2期264-268,共5页
Journal of Zhejiang University：Engineering Science
关键词
二手房
径向基函数网络
价格评估
Economics
Finance
Learning systems
Radial basis function networks
