The fuzzy logic accepts infinite intermediate logical values between false and true. In view of this principle, a system based on fuzzy rules was established to provide the best management of Catasetum fimbriatum. For the input of the developed fuzzy system, temperature and shade variables were used, and for the output, the orchid vitality. The system may help orchid experts and amateurs to manage this species. "Low" (L), "Medium" (M) and "High" (H) were used as linguistic variables. The objective of the study was to develop a system based on fuzzy rules to improve management of the Catasetum fimbriatum species, as its production presents some difficulties, and it offers high added value.
RESUMOA lógica fuzzy admite infinitos valores lógicos intermediários entre o falso e o verdadeiro. Com esse princípio, foi elaborado neste trabalho um sistema baseado em regras fuzzy, que indica a melhor forma de manejar a espécie Catasetum fimbriatum. O sistema fuzzy desenvolvido teve como entradas as variáveis temperatura e sombreamento, e a saída à vitalidade das orquídeas, que poderá auxiliar os orquidófilos no manejo da espécie, e foram utilizadas as variáveis linguísticas "Baixo" (B), "Médio" (M) e "Alto" (A). O objetivo deste trabalho é desenvolver um sistema baseado em regras fuzzy para auxiliar no manejo da espécie Catasetum fimbriatum, pois se trata de uma espécie de difícil cultivo e de alto valor agregado.Palavras-chave: Manejo, cultivar, habitat e sistemas Fuzzy
The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.
The Body Mass Index (BMI) can be used by farmers to help determine the time of evaluation of the body mass gain of the animal. However, the calculation of this index does not reveal immediately whether the animal is ready for slaughter or if it needs special care fattening. The aim of this study was to develop a software using the Fuzzy Logic to compare the bovine body mass among themselves and identify the groups for slaughter and those that requires more intensive feeding, using "mass" and "height" variables, and the output Fuzzy BMI. For the development of the software, it was used a fuzzy system with applications in a herd of 147 Nellore cows, located in a city of Santa Rita do Pardo city -Mato Grosso do Sul (MS) state, in Brazil, and a database generated by Matlab software.KEYWORDS: computer system, IMC, Mamdani and profits.
SOFTWARE PARA A AVALIAÇÃO DE GANHO CORPORAL DE REBANHO NELORE PELO ÍNDICE DE MASSA CORPORAL FUZZYRESUMO: O Índice de Massa Corporal (IMC) pode ser utilizado por pecuaristas para auxiliar na determinação do momento da avaliação de ganho corporal do animal. No entanto, o cálculo desse índice não revela imediatamente se o animal está apto ao abate ou se necessita de cuidados especiais para recuperação. O objetivo deste trabalho foi desenvolver um software utilizando a lógica fuzzy para a comparação da massa corporal de bovinos entre si e identificação dos grupos para abate, e dos que necessitam de alimentação mais intensa, utilizando-se das variáveis "massa" e "altura", e a saída IMCFuzzy. Para a elaboração do software, utilizou-se de um sistema fuzzy com aplicações em um rebanho de 147 vacas nelore, localizado em Santa Rita do Pardo-MS, e um banco de dados gerado pelo software Matlab.
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