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dc.contributor.authorDeng, Daen_NZ
dc.contributor.authorKasabov, Nikolaen_NZ
dc.date.available2011-04-07T03:06:11Z
dc.date.copyright2000-03en_NZ
dc.identifier.citationDeng, D., & Kasabov, N. (2000). Evolving self-organizing maps for on-line learning, data analysis and modelling (Information Science Discussion Papers Series No. 2000/06). University of Otago. Retrieved from http://hdl.handle.net/10523/1033en
dc.identifier.urihttp://hdl.handle.net/10523/1033
dc.description.abstractIn real world information systems, data analysis and processing are usually needed to be done in an on-line, self-adaptive way. In this respect, neural algorithms of incremental learning and constructive network models are of increased interest. In this paper we present a new algorithm of evolving self-organizing map (ESOM), which features fast one-pass learning, dynamic network structure, and good visualisation ability. Simulations have been carried out on some benchmark data sets for classification and prediction tasks, as well as on some macroeconomic data for data analysis. Compared with other methods, ESOM achieved better classification with much shorter learning time. Its performance for time series modelling is also comparable, requiring more hidden units but with only one-pass learning. Our results demonstrate that ESOM is an effective computational model for on-line learning, data analysis and modelling.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleEvolving self-organizing maps for on-line learning, data analysis and modellingen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages16en_NZ
otago.date.accession2010-10-26 20:27:59en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints971en_NZ
otago.school.eprintsKnowledge Engineering Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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otago.relation.number2000/06en_NZ
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