Use este identificador para citar ou linkar para este item: https://locus.ufv.br//handle/123456789/12686
Tipo: Artigo
Título: Evaluation of the efficiency of artificial neural networks for genetic value prediction
Autor(es): Silva, G.N.
Tomaz, R.S.
Sant’Anna, I.C.
Carneiro, V.Q.
Cruz, C.D.
Nascimento, M.
Abstract: Artificial neural networks have shown great potential when applied to breeding programs. In this study, we propose the use of artificial neural networks as a viable alternative to conventional prediction methods. We conduct a thorough evaluation of the efficiency of these networks with respect to the prediction of breeding values. Therefore, we considered eight simulated scenarios, and for the purpose of genetic value prediction, seven statistical parameters in addition to the phenotypic mean in a network designed as a multilayer perceptron. After an evaluation of different network configurations, the results demonstrated the superiority of neural networks compared to estimation procedures based on linear models, and indicated high predictive accuracy and network efficiency.
Palavras-chave: Artificial intelligence
Simulation
Accuracy
Editor: Genetics and Molecular Research
Tipo de Acesso: Open Access
URI: http://dx.doi.org/10.4238/gmr.15017676
http://www.locus.ufv.br/handle/123456789/12686
Data do documento: 28-Mar-2016
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