ANN+GIS: An automated system for property valuation

Authors:
Noelia García;Matías Gámez;Esteban Alfaro
Affiliations:
Faculty of Business and Economics, University of Castilla-La Mancha, Plaza de la Universidad 1, 02071 Albacete, Spain;Faculty of Business and Economics, University of Castilla-La Mancha, Plaza de la Universidad 1, 02071 Albacete, Spain;Faculty of Business and Economics, University of Castilla-La Mancha, Plaza de la Universidad 1, 02071 Albacete, Spain
Venue:
Neurocomputing
Year:
2008

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Abstract

Although property valuation models have become an important paradigm in real estate market research, the results of the most well-known approaches are limited due to various data-related problems such as the non-linearity of relationships, the presence of noise, or the absence of necessary information. This paper focuses on overcoming these obstacles. We introduce an automated system for property valuation that combines artificial neural network models with a geographic information system, and both tools have shown their potential usefulness in the field of economic research. The artificial neural network models used in this work are the multilayer perceptron, the radial basis function, and Kohonen's maps.