Journal article

A neural network based model for real estate price estimation considering environmental quality of property location

Real estate Consumer behaviour Housing location Pollution Machine learning residential property Behavioural economics Italy
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In this paper, a model based on Artificial Neural Network (ANN) has been applied to real estate appraisal. Moreover, an evaluation of ANN performances in estimating the sale price of residential properties has been carried out. Artificial Neural Networks (ANNs) are useful in modelling input-output relationships learning directly from observed data. This capability can be very useful in complex systems like the real estate ones where motivations, tastes and budget availability often do not follow rational behaviours. This study also analyses the impact of such key environmental conditions that represent a problem related to many industrial cities where pollution and landscaping consequences affect the real estate market and residential location choices. We have considered a set of asking price’s houses collected in the urban area of Taranto (Italy) where the biggest European steel factory and the 2nd industrial harbour are located.

(17th Meeting of the EURO Working Group on Transportation, EWGT2014, 2-4 July 2014,  Sevilla, Spain) 

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