Fuzzy logic is a powerful tool for the automation of milk classification
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
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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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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1823248244901150720 |