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International Conference on Computational Science and Its Applications

ICCSA 2015: Computational Science and Its Applications -- ICCSA 2015 pp 194–209Cite as

Property Valuations in Times of Crisis: Artificial Neural Networks and Evolutionary Algorithms in Comparison

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9157))

Abstract

In the current economic situation, characterized by a high uncertainty in the appraisal of property values, the need of “slender” models able to operate even on limited data, to automatically capture the causal relations between explanatory variables and selling prices and to predict property values in the short term, is increasingly widespread. In addition to Artificial Neural Networks (ANN), that satisfy these prerogatives, recently, in some fields of Civil Engineering an hybrid data-driven technique has been implemented, called Evolutionary Polynomial Regression (EPR), that combines the effectiveness of Genetic Programming with the advantage of classical numerical regression. In the present paper, ANN methods and the EPR procedure are compared for the construction of estimation models of real estate market values. With reference to a sample of residential apartments recently sold in a district of the city of Bari (Italy), two estimation models of market value are implemented, one based on ANN and another using EPR, in order to test the respective performance. The analysis has highlighted the preferability of the EPR model in terms of statistical accuracy, empirical verification of results obtained and reduction of the complexity of the mathematical expression.

The work must be attributed in equal parts to the authors.

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Author information

Authors and Affiliations

  1. Department of Science of Civil Engineering and Architecture, Polytechnic of Bari, Bari, Italy

    Francesco Tajani & Pierluigi Morano

  2. Department of Architecture and Design, University “Sapienza”, Rome, Italy

    Marco Locurcio & Nicola D’Addabbo

Authors
  1. Francesco Tajani
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  2. Pierluigi Morano
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  3. Marco Locurcio
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  4. Nicola D’Addabbo
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Corresponding author

Correspondence to Pierluigi Morano .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Canaanland, Nigeria

    Sanjay Misra

  4. University of Calgary, Calgary, Alberta, Canada

    Marina L. Gavrilova

  5. University of Minho, Braga, Portugal

    Ana Maria Alves Coutinho Rocha

  6. Polytechnic University, Bari, Italy

    Carmelo Torre

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

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Tajani, F., Morano, P., Locurcio, M., D’Addabbo, N. (2015). Property Valuations in Times of Crisis: Artificial Neural Networks and Evolutionary Algorithms in Comparison. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9157. Springer, Cham. https://doi.org/10.1007/978-3-319-21470-2_14

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  • DOI: https://doi.org/10.1007/978-3-319-21470-2_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21469-6

  • Online ISBN: 978-3-319-21470-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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