Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409240 | Neurocomputing | 2008 | 10 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Noelia García, Matías Gámez, Esteban Alfaro,