Title of article :
A comparison of neural network and multiple regression predictions for 305-day lactation yield using partial lactation records
Author/Authors :
Lacroix، R. نويسنده , , Wojcik، J. نويسنده , , Grzesiak، W. نويسنده , , Blaszczyk، P. نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2003
Pages :
-306
From page :
307
To page :
0
Abstract :
Milk yield predictions based on artificial neural etworks and multiple regression were studied. The 305-d lactation yield predictions were based on milk yield of the first 4 test days. Average 305-d milk production of the herd, number of days in milk and month of calving. The predictions made with either the neural network or the multiple regression model did not differ (P > 0.05) from the values estimated with the current Polish dairy cattle evaluation system. The neural network model may be alternative method of predicting these traits.
Keywords :
Multiple linear regression , Artificial neural networks , milk yield prediction , test day data
Journal title :
CANADIAN JOURNAL OF ANIMAL SCIENCE
Serial Year :
2003
Journal title :
CANADIAN JOURNAL OF ANIMAL SCIENCE
Record number :
81367
Link To Document :
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