Comparison of Artificial Neural Network and Multiple Regression Analysis for Prediction of Fat Tail Weight of Sheep

Authors

  • M. Vakili Alavijeh Department of Mathematics, Faculty of Mathematical Science, Shahid Beheshti University, Tehran, Iran
  • M.A. Norouzian Department of Animal Science, College of Abouraihan, University of Tehran, Tehran, Iran
Abstract:

A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the training set comprising of 75 percent data (52 records) to build the neural network model and test data set comprising of 25 percent (17 records), which is not used during the training and is used to evaluate performance of different models. The mean relative error was significantly (P

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Journal title

volume 6  issue 4

pages  895- 900

publication date 2016-12-01

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