Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture

Detalhes bibliográficos
Autor(a) principal: Góes, Bruno César
Data de Publicação: 2020
Outros Autores: Goes, Renato Jaqueto, Cremasco, Camila Pires, Gabriel Filho, Luís Roberto Almeida
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/8938
Resumo: Fuzzy logic was introduced into the scientific world in the 1960s by the then mathematician Lotif Asker Zadeh. Its concept is based on the non-probabilistic uncertainty principle approach, composed of subjectivity and imprecision in the linguistic terms of the information, assigning values for the degree of relevance between 0 and 1. Fuzzy logic is present in the most diverse fields of activity, from aircraft construction to widespread use in the medical field. Thus, its use has been intensifying in the field of agrarian sciences, as it has a greater degree of accuracy in relation to statistical models, carried out by agronomic experiments. The objective was to carry out a didactic description of the fuzzy methodology used to build a fuzzy system applied to soybean cultivated under no-tillage system. For modeling, the MATLAB R2019a software was used, in which the screen was printed for each step during the construction of the model, in order to contribute to the wide dissemination of fuzzy systems in agricultural sciences.
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spelling Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean cultureMétodo de uso del software Fuzzy Logic Toolbox de MATLAB para el modelado matemático de variables biométricas y nutricionales del cultivo de sojaMétodo de utilização do Fuzzy Logic Toolbox do software MATLAB para modelagem matemática de variáveis biométricas e nutricionais da cultura da sojaArtificial intelligenceFuzzy systemsFuzzy logic.Inteligencia artificialSistema difusoLógica difusa.Inteligência artificialSistema fuzzyLógica fuzzy.Fuzzy logic was introduced into the scientific world in the 1960s by the then mathematician Lotif Asker Zadeh. Its concept is based on the non-probabilistic uncertainty principle approach, composed of subjectivity and imprecision in the linguistic terms of the information, assigning values for the degree of relevance between 0 and 1. Fuzzy logic is present in the most diverse fields of activity, from aircraft construction to widespread use in the medical field. Thus, its use has been intensifying in the field of agrarian sciences, as it has a greater degree of accuracy in relation to statistical models, carried out by agronomic experiments. The objective was to carry out a didactic description of the fuzzy methodology used to build a fuzzy system applied to soybean cultivated under no-tillage system. For modeling, the MATLAB R2019a software was used, in which the screen was printed for each step during the construction of the model, in order to contribute to the wide dissemination of fuzzy systems in agricultural sciences.La lógica difusa fue introducida en el mundo científico en la década de 1960 por el entonces matemático Lotif Asker Zadeh. Su concepto se basa en el enfoque del principio de incertidumbre no probabilístico, compuesto por subjetividad e imprecisión en los términos lingüísticos de la información, asignando valores para el grado de relevancia entre 0 y 1. La lógica difusa está presente en los más diversos campos de actividad, desde la construcción de aeronaves hasta su uso generalizado en el campo médico. Así, su uso se ha ido intensificando en el campo de las ciencias agrarias, ya que posee un mayor grado de precisión en relación a los modelos estadísticos, realizados mediante experimentos agronómicos. El objetivo fue realizar una descripción didáctica de la metodología difusa utilizada para construir un sistema difuso aplicado a soja cultivada bajo sistema de labranza cero. Para el modelado se utilizó el software MATLAB R2019a, en el cual se imprimió la pantalla de cada paso durante la construcción del modelo, con el fin de contribuir a la amplia difusión de los sistemas difusos en las ciencias agrícolas.A lógica fuzzy foi introduzida no meio científico na década de 1960 pelo então matemático Lotif Asker Zadeh. Seu conceito baseia-se na abordagem do princípio da incerteza não probabilística, composta de subjetividade e imprecisão nos termos linguísticos da informação, atribuindo valores para o grau de pertinência entre 0 e 1. A lógica fuzzy está presente nos mais diversos campos de atuação, desde construção de aeronaves à ampla utilização na área médica. Dessa forma, seu uso vem se intensificando no campo das ciências agrárias, dado possuir maior grau de acerto em relação aos modelos estatísticos, realizados de experimentos agronômicos. O objetivo foi realizar uma descrição didática da metodologia fuzzy utilizada para construção de um sistema fuzzy aplicado na cultura da soja cultivada em sistema plantio direto. Para modelagem foi utilizado o software MATLAB R2019a, no qual foi realizado “print” da tela de cada passo durante a construção do modelo, de modo a contribuir para ampla divulgação dos sistemas fuzzy nas ciências agrárias.Research, Society and Development2020-10-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/893810.33448/rsd-v9i10.8938Research, Society and Development; Vol. 9 No. 10; e4329108938Research, Society and Development; Vol. 9 Núm. 10; e4329108938Research, Society and Development; v. 9 n. 10; e43291089382525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/8938/7774Copyright (c) 2020 Bruno César Góes; Renato Jaqueto Goes; Camila Pires Cremasco; Luís Roberto Almeida Gabriel Filhohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGóes, Bruno CésarGoes, Renato Jaqueto Cremasco, Camila PiresGabriel Filho, Luís Roberto Almeida2020-10-31T12:03:23Zoai:ojs.pkp.sfu.ca:article/8938Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:31:18.128476Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
Método de uso del software Fuzzy Logic Toolbox de MATLAB para el modelado matemático de variables biométricas y nutricionales del cultivo de soja
Método de utilização do Fuzzy Logic Toolbox do software MATLAB para modelagem matemática de variáveis biométricas e nutricionais da cultura da soja
title Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
spellingShingle Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
Góes, Bruno César
Artificial intelligence
Fuzzy systems
Fuzzy logic.
Inteligencia artificial
Sistema difuso
Lógica difusa.
Inteligência artificial
Sistema fuzzy
Lógica fuzzy.
title_short Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
title_full Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
title_fullStr Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
title_full_unstemmed Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
title_sort Method of using the Fuzzy Logic Toolbox of MATLAB software for mathematical modeling of biometric and nutritional variables of soybean culture
author Góes, Bruno César
author_facet Góes, Bruno César
Goes, Renato Jaqueto
Cremasco, Camila Pires
Gabriel Filho, Luís Roberto Almeida
author_role author
author2 Goes, Renato Jaqueto
Cremasco, Camila Pires
Gabriel Filho, Luís Roberto Almeida
author2_role author
author
author
dc.contributor.author.fl_str_mv Góes, Bruno César
Goes, Renato Jaqueto
Cremasco, Camila Pires
Gabriel Filho, Luís Roberto Almeida
dc.subject.por.fl_str_mv Artificial intelligence
Fuzzy systems
Fuzzy logic.
Inteligencia artificial
Sistema difuso
Lógica difusa.
Inteligência artificial
Sistema fuzzy
Lógica fuzzy.
topic Artificial intelligence
Fuzzy systems
Fuzzy logic.
Inteligencia artificial
Sistema difuso
Lógica difusa.
Inteligência artificial
Sistema fuzzy
Lógica fuzzy.
description Fuzzy logic was introduced into the scientific world in the 1960s by the then mathematician Lotif Asker Zadeh. Its concept is based on the non-probabilistic uncertainty principle approach, composed of subjectivity and imprecision in the linguistic terms of the information, assigning values for the degree of relevance between 0 and 1. Fuzzy logic is present in the most diverse fields of activity, from aircraft construction to widespread use in the medical field. Thus, its use has been intensifying in the field of agrarian sciences, as it has a greater degree of accuracy in relation to statistical models, carried out by agronomic experiments. The objective was to carry out a didactic description of the fuzzy methodology used to build a fuzzy system applied to soybean cultivated under no-tillage system. For modeling, the MATLAB R2019a software was used, in which the screen was printed for each step during the construction of the model, in order to contribute to the wide dissemination of fuzzy systems in agricultural sciences.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/8938
10.33448/rsd-v9i10.8938
url https://rsdjournal.org/index.php/rsd/article/view/8938
identifier_str_mv 10.33448/rsd-v9i10.8938
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/8938/7774
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 9 No. 10; e4329108938
Research, Society and Development; Vol. 9 Núm. 10; e4329108938
Research, Society and Development; v. 9 n. 10; e4329108938
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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