Fuzzy logic is a powerful tool for the automation of milk classification

Detalhes bibliográficos
Autor(a) principal: Jousiane Alves Martins
Data de Publicação: 2022
Outros Autores: Alcinei Místico Azevedo, Anna Cristina de Almeida, Luana Cristina Rodrigues da Silva, Ana Clara Gonçalves Fernandes, Nermy Ribeiro Valadares, Ignacio Aspiazu
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://doi.org/10.4025/actascitechnol.v44i1.57860
http://hdl.handle.net/1843/59589
https://orcid.org/0000-0001-5196-0851
Resumo: The demand for the consumption of milk and dairy products by the consumer market is very high. This makes it difficult to analyze the large number of milk samples for quality. In addition to the requirement to consider many quality attributes, there are usually large number of producers, who need daily milk evaluations. The aim of the study was to evaluate the efficiency of fuzzy logic in decision making for the classification of milk. In the fuzzification stage, physical and chemical characteristics of the milk were considered as input linguistic variables. For each linguistic variable, pertinence functions were created, and these were made considering the trapezoidal forms. In the inference stage, rules were established for the association of linguistic variables and output variables (adulterated, inadequate and adequate). To verify the efficiency of the modeled system, 1,000 adulterated, inadequate and adequate milk samples were computationally simulated. Precision was verified when automating decision making in the classification of milk by the fuzzy logic, totaling 100% of correctness. Therefore, the fuzzy system is an efficient tool for the classification of milk and can be used advantageously by professionals in the field in order to reduce human and financial resources.
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spelling Fuzzy logic is a powerful tool for the automation of milk classificationInteligência computacionalLógica difusaDerivados do leiteLeite -- AdulteraçãoThe demand for the consumption of milk and dairy products by the consumer market is very high. This makes it difficult to analyze the large number of milk samples for quality. In addition to the requirement to consider many quality attributes, there are usually large number of producers, who need daily milk evaluations. The aim of the study was to evaluate the efficiency of fuzzy logic in decision making for the classification of milk. In the fuzzification stage, physical and chemical characteristics of the milk were considered as input linguistic variables. For each linguistic variable, pertinence functions were created, and these were made considering the trapezoidal forms. In the inference stage, rules were established for the association of linguistic variables and output variables (adulterated, inadequate and adequate). To verify the efficiency of the modeled system, 1,000 adulterated, inadequate and adequate milk samples were computationally simulated. Precision was verified when automating decision making in the classification of milk by the fuzzy logic, totaling 100% of correctness. Therefore, the fuzzy system is an efficient tool for the classification of milk and can be used advantageously by professionals in the field in order to reduce human and financial resources.Universidade Federal de Minas GeraisBrasilICA - INSTITUTO DE CIÊNCIAS AGRÁRIASUFMG2023-10-18T11:35:40Z2023-10-18T11:35:40Z2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://doi.org/10.4025/actascitechnol.v44i1.578601807-8664http://hdl.handle.net/1843/59589https://orcid.org/0000-0001-5196-0851engActa Scientiarum. TechnologyJousiane Alves MartinsAlcinei Místico AzevedoAnna Cristina de AlmeidaLuana Cristina Rodrigues da SilvaAna Clara Gonçalves FernandesNermy Ribeiro ValadaresIgnacio Aspiazuinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2023-10-18T20:33:42Zoai:repositorio.ufmg.br:1843/59589Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2023-10-18T20:33:42Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.none.fl_str_mv Fuzzy logic is a powerful tool for the automation of milk classification
title Fuzzy logic is a powerful tool for the automation of milk classification
spellingShingle Fuzzy logic is a powerful tool for the automation of milk classification
Jousiane Alves Martins
Inteligência computacional
Lógica difusa
Derivados do leite
Leite -- Adulteração
title_short Fuzzy logic is a powerful tool for the automation of milk classification
title_full Fuzzy logic is a powerful tool for the automation of milk classification
title_fullStr Fuzzy logic is a powerful tool for the automation of milk classification
title_full_unstemmed Fuzzy logic is a powerful tool for the automation of milk classification
title_sort Fuzzy logic is a powerful tool for the automation of milk classification
author Jousiane Alves Martins
author_facet Jousiane Alves Martins
Alcinei Místico Azevedo
Anna Cristina de Almeida
Luana Cristina Rodrigues da Silva
Ana Clara Gonçalves Fernandes
Nermy Ribeiro Valadares
Ignacio Aspiazu
author_role author
author2 Alcinei Místico Azevedo
Anna Cristina de Almeida
Luana Cristina Rodrigues da Silva
Ana Clara Gonçalves Fernandes
Nermy Ribeiro Valadares
Ignacio Aspiazu
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Jousiane Alves Martins
Alcinei Místico Azevedo
Anna Cristina de Almeida
Luana Cristina Rodrigues da Silva
Ana Clara Gonçalves Fernandes
Nermy Ribeiro Valadares
Ignacio Aspiazu
dc.subject.por.fl_str_mv Inteligência computacional
Lógica difusa
Derivados do leite
Leite -- Adulteração
topic Inteligência computacional
Lógica difusa
Derivados do leite
Leite -- Adulteração
description The demand for the consumption of milk and dairy products by the consumer market is very high. This makes it difficult to analyze the large number of milk samples for quality. In addition to the requirement to consider many quality attributes, there are usually large number of producers, who need daily milk evaluations. The aim of the study was to evaluate the efficiency of fuzzy logic in decision making for the classification of milk. In the fuzzification stage, physical and chemical characteristics of the milk were considered as input linguistic variables. For each linguistic variable, pertinence functions were created, and these were made considering the trapezoidal forms. In the inference stage, rules were established for the association of linguistic variables and output variables (adulterated, inadequate and adequate). To verify the efficiency of the modeled system, 1,000 adulterated, inadequate and adequate milk samples were computationally simulated. Precision was verified when automating decision making in the classification of milk by the fuzzy logic, totaling 100% of correctness. Therefore, the fuzzy system is an efficient tool for the classification of milk and can be used advantageously by professionals in the field in order to reduce human and financial resources.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023-10-18T11:35:40Z
2023-10-18T11:35:40Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://doi.org/10.4025/actascitechnol.v44i1.57860
1807-8664
http://hdl.handle.net/1843/59589
https://orcid.org/0000-0001-5196-0851
url http://doi.org/10.4025/actascitechnol.v44i1.57860
http://hdl.handle.net/1843/59589
https://orcid.org/0000-0001-5196-0851
identifier_str_mv 1807-8664
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Acta Scientiarum. Technology
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
Brasil
ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
UFMG
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
Brasil
ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
UFMG
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv repositorio@ufmg.br
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