DocumentCode
2712261
Title
Estimation of Housing Prices by Fuzzy Regression and Artificial Neural Network
Author
Ghodsi, Reza ; Boostani, Abtin ; Faghihi, Farshid
Author_Institution
Ind. Eng. Dept., Univ. of Tehran, Tehran, Iran
fYear
2010
fDate
26-28 May 2010
Firstpage
81
Lastpage
86
Abstract
Changes in housing prices concern both individuals and government since they have substantial influence on the socio-economic conditions. Valuations of housing are necessary in order to assess the benefit and liabilities in housing section. The housing price in Iran is based on eight economic indices. The study of trends in housing price has been made by considering the related seasonal data from 16 years ago and using the techniques of Artificial Neural Network Back propagation (ANN-Back propagation) and Fuzzy regression. The results of our experiments indicate that the estimation error (Mean Absolute Percentage Error, “MAPE”) in the ANN-Back propagation technique is less than that in Fuzzy regression. It can be shown, by comparing the estimated housing prices by applying the ANN technique with the observed ones, that the ANN technique has favorably estimated the trends in the changes of housing prices.
Keywords
Analytical models; Artificial neural networks; Asia; Computer simulation; Cost accounting; Fuzzy neural networks; Government; Industrial engineering; Linear regression; Mathematical model; Artificial Neural Network -Back propagation; Fuzzy regression; Housing prices; Mean Absolute Percentage Error;
fLanguage
English
Publisher
ieee
Conference_Titel
Mathematical/Analytical Modelling and Computer Simulation (AMS), 2010 Fourth Asia International Conference on
Conference_Location
Kota Kinabalu, Malaysia
Print_ISBN
978-1-4244-7196-6
Type
conf
DOI
10.1109/AMS.2010.29
Filename
5489661
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