Rearsch on Selecting Real Estate Project Based on PCA and RBF Neural Network

被引：0
|
作者：
Zhao Hui [1 ]
Chen Li-ming [1 ]
机构：
[1] Qingdao Technol Univ, Sch Management, Qingdao, Peoples R China
来源：
ADVANCED RESEARCH ON AUTOMATION, COMMUNICATION, ARCHITECTONICS AND MATERIALS, PTS 1 AND 2 | 2011年 / 225-226卷 / 1-2期
关键词：
Real estate project; PCA; RBF;
D O I：
10.4028/www.scientific.net/AMR.225-226.162
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new method based on the integration of principal component analysis (PCA) and radial basic function (RBF) neural network is put forward for selecting the real estate project. Firstly, principal component analysis (PCA) is used to reduce the evaluation index dimensions. And then, radial basic function (RBF) neural network is used to evaluate the real estate projects. In order to grasp this method better, finally, the paper provides a case to demonstrate the application of this method in selecting the real estate project. The case has shown that the method applied to select the real estate project is feasible and reliable.
引用
收藏
页码：162 / 165
页数：4
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