Comput Math Methods Med - Prediction of breeding values for dairy cattle using artificial neural networks and neuro-fuzzy systems.

Tópicos

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Resumo

Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV) of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP) with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production.

Resumo Limpo

develop machin learn soft comput techniqu provid mani opportun research establish new analyt method differ area scienc object studi investig potenti two type intellig learn method artifici neural network neurofuzzi system order estim breed valu ebv iranian dairi cattl initi breed valu lactat holstein cow milk fat yield estim use convent best linear unbias predict blup anim model establish multilay perceptron use build ann predict breed valu perform data select candid subsequ fuzzi logic use form nfs hybrid intellig system implement via local linear model tree algorithm milk yield correl ebv ebv predict ann nfs respect correspond correl fat yield respect correl multitrait predict ebv milk fat yield predict simultan ann respect wherea correspond correl refer ebv multitrait nfs respect milk fat product

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