| Research Abstract |
In order to obtain basic information for the construction of a livestock management support system using neural network, a simulation of growth prediction of bred swine was conducted using 3 layred back-propagation network. In addition to this, a simulation of growth prediction using linear multiple regression model was also carried out to compare with the result of the simulation using neural network model.
As a first step of the study, seven growth prediction factors such as genealogy, sex, birth weight, intake of digestive energy, average house temperature and others were selected, and the simulation of growth prediction using neural network was carried out by changing the number of hidden units and learning cycles of the network.
As the results of these simulations, the percentage of apparent prediction level of neural network model was about 1-11% higher than that of linear multiple regression model, and it was clarified that the use of neural network was effective for growth prediction of swine.
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