Author/Authors :
Ghazanfari، S نويسنده Department of Animal and Poultry Science, College of Aboureihan, University of Tehran, Tehran, Iran Ghazanfari, S , Nobari، K نويسنده Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran Nobari, K , Tahmoorespur، M نويسنده Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran Tahmoorespur, M
Abstract :
Artificial neural networks (ANN) have shown to be a powerful tool for system modeling in a wide range of applications. The focus of this study is on neural network applications to data analysis in egg production. An ANN model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variables. High R2 and T for ANN model revealed that ANN is an efficient method of predicting egg production for pullet and hen flocks. We also estimated ANN parameters of a number of eggs on four data sets of individual hens. By increasing the summary intervals to 2 wk, 4 wk and then to 6 wk, ANN power was increased for prediction of egg produc-tion. The results suggested that the ANN model could provide an effective means of recognizing the pat-terns in data and accurately predicting the egg production of laying hens based on investigating their age.
