| Autor: |
Rahman, Mokidur, Mandal, Ajoy, Gayari, Indrajit, Bidyalaxmi, Kangabam, Sarkar, Debajyoti, Allu, Teja, Debbarma, Asish |
| Předmět: |
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| Zdroj: |
Biological Rhythm Research; Feb2023, Vol. 54 Issue 2, p249-262, 14p |
| Abstrakt: |
Early prediction of livestock productivity in any livestock enterprise provides valuable information to adopt strategic farm management for economic and profitable livestock production. Therefore, researchers developed and implemented different mathematical tools to establish the accuracy of prediction. However, due to the complexity of data sets and high-order non-linearity among the individuals concerning different production traits, the accuracy of forecasting livestock productivity is a tedious job. With this context, the artificial neural network (ANN), a machine learning program, gained popularity in the field of animal science due to its robust and effective handling of the complexity of a large datasets. The present review aims to discuss the potential utility of artificial neural networks in the different fields of livestock farming for improving livestock productivity as well as for the efficient farm management practices for economic and sustainable livestock production. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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