The Application of Genetic Programming in Milk Yield Prediction for Dairy Cows

Authors:
Chaochang Chiu;Jih-Tay Hsu;Chih-Yung Lin
Affiliations:
-;-;-
Venue:
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Year:
2000

Citing 3
Cited 0

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Journal of Management Information Systems - Special section: Information technology and its organizational impact

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Abstract

Milk yield forecasting can help dairy farmers to deal with the continuously changing condition all year round and to reduce the unnecessary overheads. Several variables (somatic cell count, pariety, day in milk, milk protein content, milk fat content, season) related to milk yield are collected as the parameters of the forecasting model. The use of an improved Genetic Programming (GP) technique with dynamic learning operators is proposed and achieved with acceptable prediction results.