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dc.contributor.authorCruz Corona, Carlos Alberto 
dc.contributor.authorRodríguez Ramos, Adrián
dc.contributor.authorBernal de Lázaro, José M.
dc.contributor.authorLlanes Santiago, Orestes
dc.contributor.authorDa Silva Neto, Antônio José
dc.date.accessioned2024-02-08T11:43:50Z
dc.date.available2024-02-08T11:43:50Z
dc.date.issued2022
dc.identifier.citationRAMOS AR, LÁZARO JMB, CORONA CC, SILVA NETO AJ & LLANES-SANTIAGO O. 2022. An approach to robust condition monitoring in industrial processes using pythagorean membership grades. An Acad Bras Cienc 94: e20200662es_ES
dc.identifier.urihttps://hdl.handle.net/10481/88725
dc.description.abstractIn this paper, a robust approach to improve the performance of a condition monitoring process in industrial plants by using Pythagorean membership grades is presented. The FCM algorithm is modified by using Pythagorean fuzzy sets, to obtain a new variant of it called Pythagorean Fuzzy C-Means (PyFCM). In addition, a kernel version of PyFCM (KPyFCM) is obtained in order to achieve greater separability among classes, and reduce classification errors. The approach proposed is validated using experimental datasets and the Tennessee Eastman (TE) process benchmark. The results are compared with the results obtained with other algorithms that use standard and non-standard membership grades. The highest performance obtained by the approach proposed indicate its feasibility.es_ES
dc.description.sponsorshipTIN2017-86647-P from the Spanish Ministry of Economy and Competitivenes, including FEDER fundses_ES
dc.description.sponsorshipFundacão Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)es_ES
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)es_ES
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (Finance Code 001) provided by the project CAPES-PRINT Process No. 88881.311758/2018-01,es_ES
dc.description.sponsorshipUniversidad Tecnológica de La Habana José Antonio Echeverría, Cubaes_ES
dc.language.isoenges_ES
dc.publisherAnais da Academia Brasileira de Ciênciases_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleAn approach to robust condition monitoring in industrial processes using pythagorean membership gradeses_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1590/0001-3765202220200662
dc.type.hasVersionVoRes_ES


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