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

Abstract:

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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 and 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:

$35.00

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