Estimation of Urban housing Price by Using Hedonic and Artificial Neural Networks; (Case Study Koye Valiaser, Tabriz)

Housing as a heterogeneous product, durable, immovable,capitalist, useable, with lateral effects has dedicated itself a large part of family budget and also has a great role in the occupation and value added of the countries.Then prediction of the housing price has a great importance among the urban planners and decision makers. If this prediction be able to provide the main factors which affect the housing price, then it will be a good instrument for decision making. If this estimation, particularly be able to reflect suitably the share of effective factors on the housing value, then it can be used in the urban and regional policy making. With respect to the importance of the issue, this article intends to investigate the main factors which affect on the housing price of the Koye Valiaser in the Tabriz. It is common to use hedonic regression and neural networks as a multi regression methods for predicating the housing price. For providing the effective factors we got help from Delphi method and the data gathered from questioner survey. Both Hedonic and Artificial Neural network could predicate the price. But the accuracy of neural network was much better than the Hedonic. Also the research showed there is relation among the spatial factors and the price of housing in Koye Valiaser.