application of linear regression and artificial neuralnetwork for broiler chicken growth performance prediction

this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kcal/kg) and crude protein (g/kg) and outputs of feed intake, weight gain and feed conversion ratio variables. high r2 and t values for the ann model in comparison to linear regression revealed that the artificial neural network (ann) is an efficient method for growth performance prediction in the starter period for broiler chickens. this study also focused on expanding the experiment with more levels of inputs to predict outputs the using best ann model.