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Bayesian neural network learning for prediction in the Australian dairy industry

Macrossan, Paula E. and Abbass, Hussein A. and Mengersen, Kerrie L. and Towsey, Michael W. and Finn, Gerard (1999) Bayesian neural network learning for prediction in the Australian dairy industry. In Hand, D.J. and Kok, J.N. and Berthold, M.R., Eds. Proceedings Third International Symposium on Intelligent Data Analysis (IDA'99) Lecture Notes in Computer Science, LNCS 1642/1999, pages pp. 395-406, Netherlands.

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Abstract

One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to predict dairy daughter milk production from dairy dam, sire, herd and environmental factors. The results of the Bayesian neural network are compared with results obtained when the regression relationship is described using the traditional neural network approach. In addition, the "baseline" results of a multiple linear regression employing both frequentist and Baysian methods are presented. The potential advantages of the Bayesian neural network appraoch over the traditional neural network approach are discussed.

Item Type:Conference Paper
Status:Published
Keywords:Bayesian neural network, milk production
Subjects:280000 Information, Computing and Communication Sciences > 280200 Artificial Intelligence and Signal and Image Processing > 280212 Neural Networks, Genetic Alogrithms and Fuzzy Logic
300000 Agricultural, Veterinary and Environmental Sciences > 300400 Animal Production > 300401 Animal Breeding
ID Code:7607
Deposited By:Towsey, Michael W.
Deposited On:15 May 2007
Alternative Locations:http://dx.doi.org/10.1007/3-540-48412-4_33
Copyright Owner:Copyright 1999 Springer
Additional Information:For more information, please refer to the publisher's website (see hypertext link) or contact the author.