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
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