Genetic Algorithms and the analysis of spatially referenced data

Cooley, Roger and Hobbs, M.H.W. and Pack, Alan (1997) Genetic Algorithms and the analysis of spatially referenced data. Applied Artificial Intelligence, 11 (2). pp. 151-171. ISSN 0883-9514. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1080/088395197118299

Abstract

This article describes an application of genetic algorithms to the analysis of spatially referenced data. A genetic algorithm is used to refine the specification of an hedonic regression model of spatially distributed residential property prices. The process of refinement concerns the search for good definitions of spatially defined variables. The fitness function for the genetic algorithm is provided by the coefficient of determination of the model. The regression results produced by the refined model are compared with those produced by a model containing a set of spatially defined variables based on information provided by an expert on local property prices.

Item Type: Article
Uncontrolled keywords: genetic algorithm, spatial analysis,
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Depositing User: Mark Wheadon
Date Deposited: 25 Jul 2009 19:58
Last Modified: 16 Jul 2014 09:15
Resource URI: http://kar.kent.ac.uk/id/eprint/21529 (The current URI for this page, for reference purposes)
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