Application of fuzzy neural network for real estate prediction

Authors:
Jian-Guo Liu;Xiao-Li Zhang;Wei-Ping Wu
Affiliations:
Department of Computer Science, Chongqing Technology and Business University, Chongqing, China;Department of Computer Science, Chongqing Technology and Business University, Chongqing, China;Department of Foreign Languages, Chongqing Technology and Business University, Chongqing, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

Citing 2
Cited 3

Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems

Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Fuzzy neural networks with application to sales forecasting

Fuzzy Sets and Systems

Determinants of house prices in Turkey: Hedonic regression versus artificial neural network

Expert Systems with Applications: An International Journal
Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics

Expert Systems with Applications: An International Journal
Bare ownership evaluation. Hedonic price model vs. artificial neural network

International Journal of Business Intelligence and Data Mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

A FNN prediction model based on hedonic price theory to estimate the appropriate price level for a new real estate is proposed. The model includes a database storing hedonic characteristics and coefficients affecting the real estate price level from recently sold projects that are representative in the local environment. The experimental result shows that the fuzzy neural network prediction model has strong function approximation ability and is suitable for real estate price prediction depending on the quality of the available data.