Estimation of Housing Prices by Fuzzy Regression and Artificial Neural Network

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.

[1]  V. Assimakopoulos,et al.  Real estate appraisal: a review of valuation methods , 2003 .

[2]  Elaine Worzala,et al.  High‐tech valuation: should artificial neural networks bypass the human valuer? , 1997 .

[3]  Stanley McGreal,et al.  Neural networks: the prediction of residential values , 1998 .

[4]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[5]  Margarita M. Lenk,et al.  An Exploration of Neural Networks and Its Application to Real Estate Valuation , 1995 .

[6]  Georg Peters Fuzzy linear regression with fuzzy intervals , 1994 .

[7]  Dorota Kuchta,et al.  Fuzzy capital budgeting , 2000, Fuzzy Sets Syst..

[8]  Antonio Terceño,et al.  Investment management in uncertainty , 2001 .

[9]  Hasan Selim,et al.  Determinants of house prices in Turkey: Hedonic regression versus artificial neural network , 2009, Expert Syst. Appl..

[10]  Rainer Schulz,et al.  A State Space Model for Berlin House Prices: Estimation and Economic Interpretation , 2003 .

[11]  Martin Hoesli,et al.  Environmental Variables and Real Estate Prices , 2001 .

[12]  Richard A. Derrig,et al.  Fuzzy Financial Pricing of Property-Liability Insurance , 1997 .

[13]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[14]  H. D. Block The perceptron: a model for brain functioning. I , 1962 .

[15]  Richard A. Derrig,et al.  Managing the Tax Liability of a Property-Liability Insurance Company by , 1999 .

[16]  Krzysztof Ostaszewski,et al.  Hedging the Tax Liability of a Property-Liability Insurance Company , 1997 .

[17]  Tom Kauko,et al.  On current neural network applications involving spatial modelling of property prices , 2003 .

[18]  A. Kaufmann,et al.  FUZZY SUBSETS APPLICATIONS IN O.R. AND MANAGEMENT , 1986 .

[19]  Lucien Duckstein,et al.  Multi-objective fuzzy regression: a general framework , 2000, Comput. Oper. Res..

[20]  J. Buckley,et al.  Fuzzy Mathematics in Finance , 1987 .

[21]  Junzo Watada,et al.  Possibilistic linear regression analysis for fuzzy data , 1989 .

[22]  C. Belvis,et al.  Fuzzy methods incorporated to the study of personal insurances , 1996, 1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report.

[23]  A. A. Mullin,et al.  Principles of neurodynamics , 1962 .

[24]  P. Werbos,et al.  Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .

[25]  Jaime Gil-Aluja Investment in Uncertainty , 1998 .

[26]  Krzysztof Ostaszewski,et al.  An Investigation into Possible Applications of Fuzzy Set Methods in Actuarial Science , 1993 .

[27]  C. R. Bector,et al.  A simple method for computation of fuzzy linear regression , 2005, Eur. J. Oper. Res..

[28]  Marvin Minsky,et al.  Perceptrons: expanded edition , 1988 .

[29]  Bernard Widrow,et al.  Adaptive switching circuits , 1988 .

[30]  Kabsung Kim,et al.  Segmentation of the Housing Market and its Determinants: Seoul and its neighbouring new towns in Korea , 2005 .

[31]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[32]  Masatoshi Sakawa,et al.  Multiobjective fuzzy linear regression analysis for fuzzy input-output data , 1992 .

[33]  M. Calzi Towards a general setting for the fuzzy mathematics of finance , 1990 .