Fuzzy simulation of bioclimatic indexes environments with and without cover for Santa Ins sheep farms
Author(s) -
Cristiane Moreira Goncalves Indira,
Pinheiro Lopes Neto Jose,
Henrique Souza Costa Jose,
de Fatima Damasceno dos Santos Luana,
Araujo Furtado Dermeval,
Wallace Barbosa do Nascimento Jose,
Romao Guerra Ricardo
Publication year - 2017
Publication title -
african journal of agricultural research
Language(s) - English
Resource type - Journals
ISSN - 1991-637X
DOI - 10.5897/ajar2017.12228
Subject(s) - fuzzy logic , cover (algebra) , relative humidity , air temperature , adaptive neuro fuzzy inference system , computer science , mathematics , simulation , environmental science , meteorology , artificial intelligence , fuzzy control system , geography , mechanical engineering , engineering
This study aimed to analyze bioclimatic indexes: black globe temperature and humidity index (BGHI) and radiant thermal load (RTL) in Santa Ines sheep farms, with and without coverage to develop a fuzzy logical computational model to forecast variables analyzed experimentally. Ten Santa Ines sheep were placed in two cover paddocks, and one without cover. Data recorded were: air temperature schedules and black globe (°C), relative humidity (%) and wind speed (m s-1), and BGHI and RTL were calculated. Computational models were developed using fuzzy logic which had as input variables, air temperature (°C) relative humidity (%) for the output variables BGHI and RTL. Based on the experimental data, there were also certain relevance curves that conform more to the results for the model generation via Fuzzy logic. The Mandani inference method was used for the preparation of rules and defuzzification of the center of gravity method was applied. The results showed that in the critical periods, 12 to 14 h, coverage was insufficient to differentiate between stress environments. It was also found that the Fuzzy models compared with the experimental data were highly correlated with R² equal to 0.99, proving it is suitable for implementation in practice. Key words: Computational model, heat stress, shelter, simulation.
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