ArticleVeterinary medicine and science2026
Application of Artificial Neural Network and the Monomolecular Model in Describing the Relationship Between Body Weight Gain and Metabolizable Energy Intake in Egg-Type Pullets.
Article in Veterinary medicine and science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundModelling growth allows nutritionists and poultry researchers to predict dynamic or daily nutrient needs more precisely than using fixed requirements.
objectivesThis study evaluated the monomolecular model and artificial neural network (ANN) to describe the relationship between metabolizable energy (ME) intake and body weight gain (BWG) in commercial strains of different egg-type pullets.
methodsA multi-layer feed-forward perceptron neural network structure was used to construct the ANN model. The best-fitted network on input data to predict BWG from ME intake in all egg-type pullets' strains was obtained with one neuron in the input layer, three neurons in the first hidden layer, two neurons in the second hidden layer and one neuron in the output layer, which was written as 1-3-2-1.
resultsThe relationship between ME intake and BWG in different egg-type pullet strains was predicted with very high accuracy by both ANN (R
conclusionsThis study demonstrated that both the monomolecular model and ANN approaches effectively described the relationship between ME intake and BWG in egg-type pullets.
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