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Genetic Algorithms and the analysis of spatially referenced data

Cooley, Roger, Hobbs, M.H.W., Pack, Alan (1997) Genetic Algorithms and the analysis of spatially referenced data. Applied Artificial Intelligence, 11 (2). pp. 151-171. ISSN 0883-9514. (doi:10.1080/088395197118299) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:21529)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
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
DOI/Identification number: 10.1080/088395197118299
Uncontrolled keywords: genetic algorithm, spatial analysis,
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 25 Jul 2009 19:58 UTC
Last Modified: 16 Feb 2021 12:32 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21529 (The current URI for this page, for reference purposes)
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