Determinants of house prices in Turkey: Hedonic regression versus artificial neural network
Expert Systems with Applications: An International Journal
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Applied Intelligence
Fuzzy wavelet networks for function learning
IEEE Transactions on Fuzzy Systems
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ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 12.05 |
In this paper, a new grading model has been developed for prediction of the selling price of house-building. Fuzzy logic systems, considering the city plans, the nearness to cultural, medical, training and educational buildings, the public transportations systems, the other environmental factors and the increased technological upgrading deals with information about construction, have been employed in order to construct the model and achieve the aim. Such factors are used as the inputs. Besides, a questionnaire application including these factors has been applied to determine the values of fuzzy training and testing sets. In this way, the constructed model has been applied to the prediction of selling prices of houses located in different regions of Eskisehir city in Turkey. The predicted values and real selling prices determined by selling market have been compared with each other. Consequently, real selling price of house-building has shown variety with respect to the regional aspects and salesmen. The suggested fuzzy logic model can be capable and usable for similar applications.