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| Brunassi,Leandro dos Anjos; Moura,Daniella Jorge de; Nääs,Irenilza de Alencar; Vale,Marcos Martinez do; Souza,Silvia Regina Lucas de; Lima,Karla Andrea Oliveira de; Carvalho,Thayla Morandi Ridolfi de; Bueno,Leda Gobbo de Freitas. |
| Production losses due to lack of precision in detecting estrus in dairy cows are well known and reported in milk production countries. Nowadays automatic estrus detection has become possible as a result of technical progress in continuously monitoring dairy cows using fuzzy pertinence functions. Dairy cow estrus is usually visually detected; however, solely use of visual detection is considered inefficient. Many studies have been carried out to develop an effective model to interpret the occurrence of estrus and detect estrus; however, most models present too many false-positive alerts and because of this they are sometimes considered unreliable. The objective of this research was to construct a system based on fuzzy inference functions evaluated with a... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Estrus cycle; Artificial intelligence; Expert system. |
| Ano: 2010 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162010000500002 |
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