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

2011 ◽  
Vol 225-226 ◽  
pp. 162-165
Author(s):  
Hui Zhao ◽  
Li Ming Chen
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Real Estate ◽  
Rbf Neural Network ◽  
Principal Component ◽  
Component Analysis ◽  
Basic Function ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Project

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.

Coordination Degree Analysis of Real Estate Investment and the National Economy in China - Based on Principal Component Analysis Method

2013 ◽  
Vol 753-755 ◽  
pp. 2870-2874
Author(s):  
Lian Fa Ruan ◽  
Long Jiang Shen
Keyword(s):  
Principal Component Analysis ◽  
Real Estate ◽  
National Economy ◽  
Principal Component ◽  
Component Analysis ◽  
Real Estate Market ◽  
Real Estate Investment ◽  
The Real ◽  
The Real Estate ◽  
Coordination Degree

Starting from six indicators like the ratio of the real estate investment growth and GDP growth etc., this article analyses the coordination degree of real estate investment and national economy with principal component analysis, and obtains the coordination index. Using 3σ method, the authors calculate the mean and standard deviation of the principal component indicator data, and then establish an early warning interval for real estate market . The results show that the real estate investment is a little excessive in recent years but the coordination degree between the real estate industry and the national economy is generally stable in China. Further investigations indicate that the change of the coordination index of the commercial housing sub-market is consistent with the whole commercial building market, but the one of the non-residential building is opposite to the total CB's.

scholarly journals Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

2021 ◽  
Vol 14 (6) ◽  
pp. 244
Author(s):  
Junjie Li ◽  
Li Zheng ◽  
Chunlu Liu ◽  
Zhifeng Shen
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
House Price ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Information Interaction ◽  
Information Spillover

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

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