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Rule extraction from artificial neural networks applied to the problem of protein secondary structure prediction

dc.contributor.advisorCechin, Adelmo Luis
dc.contributor.authorBattistella, Eduardopt_BR
dc.date.accessioned2015-03-05T13:53:43Z
dc.date.accessioned2022-09-22T19:05:06Z
dc.date.available2015-03-05T13:53:43Z
dc.date.available2022-09-22T19:05:06Z
dc.date.issued2004-03-09
dc.identifier.urihttps://hdl.handle.net/20.500.12032/56736
dc.description.abstractThis work presents a study about knowledge extraction from Neural Networks in the form of fuzzy rules. In the application of this technique, it was investigated the problem of classification of the protein secondary structure (alpha, beta and coil) from its primary structure. The implementations that make possible this task will be presented. Amongst them: the implementation of new features in the rule extraction software; the definition of a methodology for the rule extraction process; the implementation of this methodology; and the analysis of the rules. Amongst the implemented features in the rules extraction process, it will be noticed that the main point was to provide a statistical support for the knowledge extracted and to make available additional resources to measure this information. In the definition of this methodology, it will be seen that some considerations must be observed in the database preparation and in definition of the network structure. Observations that had been followed and pren
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.languagept_BRpt_BR
dc.publisherUniversidade do Vale do Rio do Sinospt_BR
dc.rightsopenAccesspt_BR
dc.subjectdata minningpt_BR
dc.subjectdata minningen
dc.titleExtração de regras de redes neurais artificiais aplicadas ao problema da determinação da estrutura secundária de proteínaspt_BR
dc.titleRule extraction from artificial neural networks applied to the problem of protein secondary structure predictionen
dc.typeDissertaçãopt_BR


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