تخمین قیمت مسکن شهر اهواز با استفاده از شبکه عصبی

In the economy of every society, housing is a basic need that should be considered. Hence, development in the housing sector has its effect on other economy sectors. So one of the significant needs of governments in the housing field is the housing price forecasts and determine the factors affecting the price of this product. The present research aimed to estimate the cost of housing and the factors affecting it in Ahwaz, fairly complete study of the neural network (multilayer perception model) to predict housing prices has done. The nature of the research is development-functional and the Way of doing it is analytical. In this research, 233 cases in 1392, according to statistics of the 16 variables were used to estimate the cost of housing. The MATLAB software was used to create an artificial neural network and finally the network with one hidden layer and 12 Nero was used. Also to determine the influence of various factors on the price of this good, it is used from the stepwise linear regression. The results indicated a 91 percent accuracy of neural network for housing price estimating in the city of Ahwaz. As well as the factors that influences the price of housing in the city infrastructure construction (size) and access to the largest accounts. Due to the high impact area of land and access is needed in planning, the construction of housing for these factors is more important than other factors.