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

• 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
• DOI: 10.33448/rsd-v9i10.8938
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/8938
• topic: Artificial intelligence; Fuzzy systems; Fuzzy logic.; Inteligencia artificial; Sistema difuso; Lógica difusa.; Inteligência artificial; Sistema fuzzy; Lógica 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.