Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels

Detalhes bibliográficos
Ano de defesa: 2024
Autor(a) principal: Fonseca, Lara Dutra lattes
Orientador(a): Aguiar, Eduardo Pestana de lattes
Banca de defesa: Fonseca, Leonardo Goliatt da lattes, Zuben, Fernando José Von lattes
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Universidade Federal de Juiz de Fora (UFJF)
Programa de Pós-Graduação: Programa de Pós-graduação em Modelagem Computacional
Departamento: ICE – Instituto de Ciências Exatas
País: Brasil
Palavras-chave em Português:
Type-2 fuzzy logic systems
Meta-heuristic optimization
Swarm intelligence
Classification
Área do conhecimento CNPq:
CNPQ::CIENCIAS EXATAS E DA TERRA
Link de acesso: https://repositorio.ufjf.br/jspui/handle/ufjf/16957
Resumo: -
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spelling Aguiar, Eduardo Pestana dehttp://lattes.cnpq.br/9530065975903052Fonseca, Leonardo Goliatt dahttp://lattes.cnpq.br/9030707448549156Zuben, Fernando José Vonhttp://lattes.cnpq.br/1756895777404187http://lattes.cnpq.br/0004406647831452Fonseca, Lara Dutra2024-07-23T17:18:59Z2024-07-222024-07-23T17:18:59Z2024-04-08https://repositorio.ufjf.br/jspui/handle/ufjf/16957-Hot box and hot wheel problems on trains are significant threats in any rail operation because they increase fatigue and wear processes, resulting in failures, costly train stoppages and even derailments. For this reason, there are many hot box and hot wheel detectors to monitor those components distributed along the railway, and when they detect overheated components, a warning is given to alert to the impending failure. However, some situations such as solar incidence, misalignment, or sensor defect can lead to improper warnings, that is, warnings that actually do not exhibit the problem. Therefore, this work develops a new model for the classification of proper and improper warnings in hot box and hot wheel problems, by the analysis of the temperatures measured in the wheels and bearings of the train when the warning was given. To this end, the discussion focuses on the use of a metaheuristic optimization algorithm into the training phase of an upper and lower singleton type-2 fuzzy logic system, in order to increase the convergence speed and the accuracy of this procedure. Thus, the performance of the new model will be based on the real data set composed of train wheel and bearing temperatures, provided by a Brazilian railway transportation company, covering several situations of proper and improper warnings. Additionally, this work presents performance analyses based on well-known data sets provided by Knowledge Extraction based on Evolutionary Learning Repository, aiming to evaluate the proposal. For comparison purposes, the results of the proposed classifier will be compared to well-know deep-learning classifiers as well as the original fuzzy model it is based on. The performance analysis of the new model is discussed in terms of classification ratio and convergence speed. The reported results show that the proposal achieved higher classification ratio and proved to be an appropriate option for the presented problem.engUniversidade Federal de Juiz de Fora (UFJF)Programa de Pós-graduação em Modelagem ComputacionalUFJFBrasilICE – Instituto de Ciências ExatasAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessCNPQ::CIENCIAS EXATAS E DA TERRAType-2 fuzzy logic systemsMeta-heuristic optimizationSwarm intelligenceClassificationSwarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional da UFJFinstname:Universidade Federal de Juiz de Fora (UFJF)instacron:UFJFCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.ufjf.br/jspui/bitstream/ufjf/16957/2/license_rdfe39d27027a6cc9cb039ad269a5db8e34MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufjf.br/jspui/bitstream/ufjf/16957/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53ORIGINALlaradutrafonseca.pdflaradutrafonseca.pdfapplication/pdf1977687https://repositorio.ufjf.br/jspui/bitstream/ufjf/16957/1/laradutrafonseca.pdf342ff826f703cf70b956c43916f1af24MD51TEXTlaradutrafonseca.pdf.txtlaradutrafonseca.pdf.txtExtracted texttext/plain68291https://repositorio.ufjf.br/jspui/bitstream/ufjf/16957/4/laradutrafonseca.pdf.txt845431fe556cb3130d2ca4ced0e219fbMD54THUMBNAILlaradutrafonseca.pdf.jpglaradutrafonseca.pdf.jpgGenerated Thumbnailimage/jpeg1157https://repositorio.ufjf.br/jspui/bitstream/ufjf/16957/5/laradutrafonseca.pdf.jpg7f1e7c3f37b970068118ea94f45be1efMD55ufjf/169572024-07-24 03:04:21.974oai:hermes.cpd.ufjf.br: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Repositório InstitucionalPUBhttps://repositorio.ufjf.br/oai/requestopendoar:2024-07-24T06:04:21Repositório Institucional da UFJF - Universidade Federal de Juiz de Fora (UFJF)false
dc.title.pt_BR.fl_str_mv Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
title Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
spellingShingle Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
Fonseca, Lara Dutra
CNPQ::CIENCIAS EXATAS E DA TERRA
Type-2 fuzzy logic systems
Meta-heuristic optimization
Swarm intelligence
Classification
title_short Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
title_full Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
title_fullStr Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
title_full_unstemmed Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
title_sort Swarm intelligence algorithm combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
author Fonseca, Lara Dutra
author_facet Fonseca, Lara Dutra
author_role author
dc.contributor.advisor1.fl_str_mv Aguiar, Eduardo Pestana de
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/9530065975903052
dc.contributor.referee1.fl_str_mv Fonseca, Leonardo Goliatt da
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/9030707448549156
dc.contributor.referee2.fl_str_mv Zuben, Fernando José Von
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/1756895777404187
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/0004406647831452
dc.contributor.author.fl_str_mv Fonseca, Lara Dutra
contributor_str_mv Aguiar, Eduardo Pestana de
Fonseca, Leonardo Goliatt da
Zuben, Fernando José Von
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS EXATAS E DA TERRA
topic CNPQ::CIENCIAS EXATAS E DA TERRA
Type-2 fuzzy logic systems
Meta-heuristic optimization
Swarm intelligence
Classification
dc.subject.por.fl_str_mv Type-2 fuzzy logic systems
Meta-heuristic optimization
Swarm intelligence
Classification
description -
publishDate 2024
dc.date.accessioned.fl_str_mv 2024-07-23T17:18:59Z
dc.date.available.fl_str_mv 2024-07-22
2024-07-23T17:18:59Z
dc.date.issued.fl_str_mv 2024-04-08
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://repositorio.ufjf.br/jspui/handle/ufjf/16957
url https://repositorio.ufjf.br/jspui/handle/ufjf/16957
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nc-nd/3.0/br/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nc-nd/3.0/br/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de Juiz de Fora (UFJF)
dc.publisher.program.fl_str_mv Programa de Pós-graduação em Modelagem Computacional
dc.publisher.initials.fl_str_mv UFJF
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv ICE – Instituto de Ciências Exatas
publisher.none.fl_str_mv Universidade Federal de Juiz de Fora (UFJF)
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFJF
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