THE USE OF ARTIFICIAL INTELLIGENCE FOR THE PREDICTION OF PRODUCTIVITY PARAMETERS IN SWINE CULTURE
AUTOR(ES)
Sangoi, Luiz Fernando, Kessler, Alexandre de Mello, Neuenfeldt Júnior, Alvaro Luiz, Siluk, Julio Cezar Mairesse, Ribeiro, Andréa Machado Leal, Soliman, Marlon
FONTE
Pesqui. Oper.
DATA DE PUBLICAÇÃO
2016-04
RESUMO
ABSTRACT In similar conditions of food handling and genetics, there are large differences in the final productivity of farms, resulting from inherent factors of the production system. This fact predisposes the need of studies on optimizing the rearing conditions of the farms, in order to verify the main limitations for the producers. Therefore, the present study aims to generate predictions of the swine productivity in the finishing phase, using variables related to their profiles and the production results achieved. 107 farmers belonging to a swine cooperative were considered in the study, located in 47 counties at the Taquari valley region, Brazil. Predictions were generated through the aid of neural networks, and the findings show that Artificial Neural Networks (ANN) can predict the productivity variables Feed Conversion, Mortality and Average Daily Gain for the proposed case.
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