Abstract

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.

Autore Pugliese

• Ottomanelli Michele

Tutti gli autori

• CHIARAZZO V. , CAGGIANI L. , MARINELLI M. , OTTOMANELLI M

Titolo volume/Rivista

TRANSPORTATION RESEARCH PROCEDIA

Anno di pubblicazione

2014

ISSN

2352-1465

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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