The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 54-176
Full Name: Kuentai Chen
Position: Assistant Professor
Age: ON
Sex: Male
Address: 84 Gungjuan Road, Taishan, New Taipei 243
Country: TAIWAN
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E-mail address: kuentai@mail.mcut.edu.tw
Other E-mails: kch5207@hotmail.com
Title of the Paper: Soft computing algorithms in Price of Taiwan Real Estates
Authors as they appear in the Paper: Hong ¡VYu Lin, Kuentai Chen
Email addresses of all the authors: hylin@mail.mcut.edu.tw, kuentai@mail.mcut.edu.tw
Number of paper pages: 10
Abstract: The prediction of real estate price is important because it concerns both individuals and government. Other than traditional statistic methods, Neural networks and Support Vector Regression have demonstrated their advantages in previous research, and thus are applied and compared in this study. Variables are first summarized and concluded from earlier research and than selected by stepwise procedure and trial-and-error methods. It is found that SVR with trial-and-error method performed the best with MAPE=4.466% and R2=0.8540. In addition, Rediscount rate, Money supply, and Price of last month are the three common variables for both BPNN and SVR. The economic explanation and relations to the housing price for selected variables are also provided.
Keywords: Forecasting, Real estate, Back propagation neural network, Data mining, Support Vector Regression
EXTENSION of the file: .pdf
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How Did you learn about congress: neural networks, real estate, prediction
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