Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/10901
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dc.contributor.authorGeorgiou, V. L.en
dc.contributor.authorPavlidis, N. G.en
dc.contributor.authorParsopoulos, K. E.en
dc.contributor.authorAlevizos, P. D.en
dc.contributor.authorVrahatis, M. N.en
dc.date.accessioned2015-11-24T17:01:17Z-
dc.date.available2015-11-24T17:01:17Z-
dc.identifier.issn0218-2130-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10901-
dc.rightsDefault Licence-
dc.subjectprobabilistic neural networksen
dc.subjectbioinformaticsen
dc.subjectparticle swarm optimizationen
dc.subjectparticle swarm optimizationen
dc.subjectlearning algorithmsen
dc.subjectconvergenceen
dc.subjectcomputationen
dc.subjecttestsen
dc.titleNew self-adaptive probabilistic neural networks in bioinformatic and medical tasksen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.publicationDate2006-
heal.abstractWe propose a self-adaptive probabilistic neural network model, which incorporates optimization algorithms to determine its spread parameters. The performance of the proposed model is investigated on two protein localization problems, as well as on two medical diagnostic tasks. Experimental results are compared with that of feedforward neural networks and support vector machines. Different sampling techniques are used and statistical tests are conducted to calculate the statistical significance of the results.en
heal.journalNameInternational Journal on Artificial Intelligence Toolsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)



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