Inteligência de enxame aplicada a problemas complexos de análise de dados: agrupamento multiobjetivo e mineração de regras de associação em data streams

Página do item simplificado
dc.contributor.advisorLopes, Fábio Silva
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/2302666201616083por
dc.contributor.authorCunha, Danilo Souza da
dc.creator.Latteshttp://lattes.cnpq.br/6968807521387651por
dc.date.accessioned2019-04-16T15:38:34Z
dc.date.accessioned2020-05-28T18:08:02Z
dc.date.available2020-05-28T18:08:02Z
dc.date.issued2019-02-19
dc.description.abstractThe increasing accumulation of data, from the most diverse sources, brings the need to develop new and robust data analysis tools. Among the many data analysis problems, two of them have been receiving special attention over the past years, both in academic and in business: multi-objective data clustering; and mining of data streams. At the same time, bio-inspired al-gorithms have been successfully applied in solving complex problems, such as those previously mentioned. It is in this context that this thesis proposes two new versions of swarm intelligence algorithms to solve these problems. More specifically, an algorithm inspired by the collective behavior of bees is used to tackle the multi-objective clustering problem, while a tool inspired by the collective decision-making of bacteria is used to mine association rules in data streams. The algorithms are potentially applicable to the cited current problems and the main thesis' contribution is the investigation of algorithms' adaptation and subsequent application to the already mentioned data mining complex problems. This document provides the theoretical basis necessary for the development and understanding of the research, introduces the algorithms, presents the results obtained, the conclusion of the performance achieved and brings a reflection of the future steps to be taken.eng
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superiorpor
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológicopor
dc.description.sponsorshipFundação de Amparo a Pesquisa do Estado de São Paulopor
dc.description.sponsorshipFundo Mackenzie de Pesquisapor
dc.formatapplication/pdf*
dc.identifier.citationCUNHA, Danilo Souza da. Inteligência de enxame aplicada a problemas complexos de análise de dados: agrupamento multiobjetivo e mineração de regras de associação em data streams. 2019. 126 f. Tese( Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo.por
dc.identifier.urihttp://dspace.mackenzie.br/handle/10899/24292
dc.keywordsswarm intelligenceeng
dc.keywordsbee colonieseng
dc.keywordsbacteria colonieseng
dc.keywordsmulti-objective clusteringeng
dc.keywordsdata streamseng
dc.keywordsassociation rule miningeng
dc.languageporpor
dc.publisherUniversidade Presbiteriana Mackenziepor
dc.rightsAcesso Abertopor
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectinteligência de enxamepor
dc.subjectcolônias de abelhaspor
dc.subjectcolônias de bactériaspor
dc.subjectagrupamento multiobjetivopor
dc.subjectregras de associaçãopor
dc.subjectfluxos de dadospor
dc.subject.cnpqCNPQ::CIENCIAS EXATAS E DA TERRApor
dc.subject.cnpqCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOpor
dc.thumbnail.urlhttp://tede.mackenzie.br/jspui/retrieve/18558/Danilo%20Souza%20da%20Cunha.pdf.jpg*
dc.titleInteligência de enxame aplicada a problemas complexos de análise de dados: agrupamento multiobjetivo e mineração de regras de associação em data streamspor
dc.typeTesepor
local.contributor.board1Oliveira, Pedro Paulo Balbi de
local.contributor.board1Latteshttp://lattes.cnpq.br/9556738277476279por
local.contributor.board2Silva, Leandro Nunes de Castro
local.contributor.board2Latteshttp://lattes.cnpq.br/2741458816539568por
local.contributor.board3Pereira, André Luiz Vizine
local.contributor.board3Latteshttp://lattes.cnpq.br/5977522212667911por
local.contributor.board4Coelho, Guilherme Palermo
local.contributor.board4Latteshttp://lattes.cnpq.br/0597865875425201por
local.publisher.countryBrasilpor
local.publisher.departmentFaculdade de Computação e Informática (FCI)por
local.publisher.initialsUPMpor
local.publisher.programEngenharia Elétricapor
Arquivos
Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
Danilo Souza da Cunha.pdf
Tamanho:
3.16 MB
Formato:
Adobe Portable Document Format
Descrição:
Baixar
Coleções
Engenharia Elétrica e Computação - Teses - EE Higienópolis