Use este identificador para citar ou linkar para este item: http://hdl.handle.net/1843/59589
Tipo: Artigo de Periódico
Título: Fuzzy logic is a powerful tool for the automation of milk classification
Autor(es): Jousiane Alves Martins
Alcinei Místico Azevedo
Anna Cristina de Almeida
Luana Cristina Rodrigues da Silva
Ana Clara Gonçalves Fernandes
Nermy Ribeiro Valadares
Ignacio Aspiazu
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.
Assunto: Inteligência computacional
Lógica difusa
Derivados do leite
Leite -- Adulteração
Idioma: eng
País: Brasil
Editor: Universidade Federal de Minas Gerais
Sigla da Instituição: UFMG
Departamento: ICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
Tipo de Acesso: Acesso Aberto
Identificador DOI: http://doi.org/10.4025/actascitechnol.v44i1.57860
URI: http://hdl.handle.net/1843/59589
Data do documento: 2022
metadata.dc.url.externa: https://periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/57860/751375154273
metadata.dc.relation.ispartof: Acta Scientiarum. Technology
Aparece nas coleções:Artigo de Periódico

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