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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chiu, C. “Dynamic Learning in Genetic Programming,” the 1999 International Conference on Artificial Intelligence (IC-AI'99), June 28-July 1, 1999, Monte Carlo Resort, Las Vegas, Nevada, USA, pp. 416–422.
Dun, S. L., Study of Lactation Curve of Holstein Lactating Cows in Taiwan, Master Thesis, National Chung Hsing University, 1980.
Dworman, G, Kimbrough, S O, and Laing, J K, “On Automated Discovery of Models using Genetic Programming: Bargaining in A Three-Agent Coalitions Game,” Journal of Management Information Systems, Vol. 12, No. 3, pp.97–125, 1996.
Holland, John H, Adaptation in Natural and Artificial Systems, University of Michigan, 1975.
Holmes, C. W., Wilson, G. F., Mackenzie, D. D. S., Flux, D. S., Brookes, I. M., and Davey, A. W. F., Milk Production from Pasture, Butterworths Agriculture Books, Wellington, New Zealand, 1987.
Hu, G. C., Analysis and Investigation of Genetic Markers of Holstein Breeding Bulls, Master Thesis, National Chung Hsing University, 1994
Jan, J. F, “Genetic Programming for Classification of Remote Sensing Data,” Taiwan Journal of Forest Science, 13(2), pp.109–118, 1998.
Koza, J. R., Genetic Programming: On the Programming of Computers by Means of Natural Selection, The MIT Press, 1982.
Lee, D G, Lee, B W, and Chang, S H, “Genetic Programming Model for Long-term Forecasting of Electric Power Demand,” Electric Power Systems Research, Vol. 40, pp. 17–22, 1997.
Mo, J. R., The Relationship of Electrical Conductivity, Somatic Cell Count, Milk Production, and Udder Status in Holstein Cows, Master Thesis, National Taiwan University, 1996
Olori, V. E., Brotherstone, S., Hill, W. G., and McGuirk, B. J., Effect of gestation stage on milk yield and composition in Holstein Friesian Dairy Cattle, Livestock Production Science, 52:167–176, 1997.
Olsson, G., Emanuelson, M., and Wiktorsson, H., Effects of Different Nutritional Levels Prepartum on the Subsequent Performance of Dairy Cows, Livestock Production Science, 53:279–290, 1998.
Schmidt, G. H., Van Vleck, L. D., and Hutjens, M. F., Principles of Dairy Science, Prentice Hall, Englewood Cliffs, New Jersey, 1988.
Skidmore, A. L., Brand, A., and Sniffen, C. J., Monitoring Milk Production: Decision Making and Follow-up, In: Brand, A., Noordhuizen, J. P. T. M., and Schukken, Y. H. (Ed.) Herd Health and Production Management in Dairy Practice. Wageningen Pers, Wageningen, The Netherlands, 1996.
Tseng, C. U., Reproduction Characteristics and Milk Yield of Holstein Dairy Cows in Taiwan, Master Thesis, National Chung Hsing University, 1992.
Wu, L. S., Effect of Age, Nutrition and Environmental Temperature on the Adrenocortical Function of Holstein Cows, Ph.D. Thesis, National Taiwan University, 1989
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chiu, C., Hsu, JT., Chih-Yung, L. (2001). The Application of Genetic Programming in Milk Yield Prediction for Dairy Cows. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_75
Download citation
DOI: https://doi.org/10.1007/3-540-45554-X_75
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43074-2
Online ISBN: 978-3-540-45554-7
eBook Packages: Springer Book Archive