Paper Title:
Research on Selecting Real Estate Project Based on PCA and RBF Neural Network
  Abstract

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.

  Info
Periodical
Advanced Materials Research (Volumes 225-226)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
162-165
DOI
10.4028/www.scientific.net/AMR.225-226.162
Citation
H. Zhao, L. M. Chen, "Research on Selecting Real Estate Project Based on PCA and RBF Neural Network", Advanced Materials Research, Vols. 225-226, pp. 162-165, 2011
Online since
April 2011
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Price
$32.00
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