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dc.contributor.authorJareanpon, C.
dc.contributor.authorPensuwon, W.
dc.contributor.authorFrank, R.
dc.contributor.authorDavey, N.
dc.date.accessioned2008-06-05T11:31:11Z
dc.date.available2008-06-05T11:31:11Z
dc.date.issued2004
dc.identifier.citationJareanpon , C , Pensuwon , W , Frank , R & Davey , N 2004 , An adaptive RBF network optimised using a genetic algorithm applied to rainfall forecasting . in In: Procs IEEE Int Symp on Communications and Information Technologies (ISCIT 2004) Vol.2 . Institute of Electrical and Electronics Engineers (IEEE) , pp. 1005-1010 . https://doi.org/10.1109/ISCIT.2004.1413871
dc.identifier.isbn0-7803-8593-4
dc.identifier.otherPURE: 86143
dc.identifier.otherPURE UUID: 2d0ca7c1-0317-4a4b-9bf5-c6e9e0f2605d
dc.identifier.otherdspace: 2299/2066
dc.identifier.otherScopus: 21844438513
dc.identifier.urihttp://hdl.handle.net/2299/2066
dc.descriptionThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. DOI : 10.1109/ISCIT.2004.1413871
dc.description.abstractRainfall prediction is a challenging task especially in a modern world facing the major environmental problem of global warming. The proposed method uses an Adaptive Radial Basis Function neural network mode with a specially designed gerietic algoruhm (CA) to obtain the optimal model parameters. A significant feature of the Adaptive Radinl Basis Function network is that it is able creak new hidden units and solve the spread factor problem using a genetic algorithm. It is shown that the evolved parameter values improved performance.en
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofIn: Procs IEEE Int Symp on Communications and Information Technologies (ISCIT 2004) Vol.2
dc.titleAn adaptive RBF network optimised using a genetic algorithm applied to rainfall forecastingen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
rioxxterms.versionofrecordhttps://doi.org/10.1109/ISCIT.2004.1413871
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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