Neural networks for animal science applications:: Two case studies

被引:27
作者
Fernandez, C.
Soria, E.
Martin, J. D.
Serrano, A. J.
机构
[1] Univ Valencia, Escola Tecn Super Engn, Dept Elect Engn, Digital Signal Proc Grp, E-46100 Valencia, Spain
[2] Univ Cardenal Herrera CEU, Fac Ciencias Expt & Salud, Dept Prod Anim, Valencia 46113, Spain
关键词
neural networks; multilayer perceptron; self-organizing map; animal science;
D O I
10.1016/j.eswa.2005.09.086
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Artificial neural networks have shown to be a powerful tool for system modelling in a wide range of applications. In this paper, we focus on neural network applications to intelligent data analysis in the field of animal science. Two classical applications of neural networks are proposed: time series prediction and clustering. The first task is related to the prediction of weekly milk production in goat flocks, which includes a knowledge discovery stage in order to analyse the relative relevance of the different variables. The second task is the clustering of goat flocks; it is used to analyse different livestock surveys by using self-organizing maps and the adaptive resonance theory, thus obtaining a qualitative knowledge from these surveys. Achieved results show the usefulness of neural networks in two animal science applications. (C) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:444 / 450
页数:7
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