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Application of Neural Networks in Animal Science
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Author(s): Emilio Soria (Valencia University, Spain), Carlos Fernández (Valencia Polytechnic University, Spain), Antonio J. Serrano (University of Valencia, Spain), Marcelino Martínez (Valencia University, Spain), José R. Magdalena (Valencia University, Spain)and Juan F. Guerrero (Valencia University, Spain)
Copyright: 2010
Pages: 17
Source title:
Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
Source Author(s)/Editor(s): Emilio Soria Olivas (University of Valencia, Spain), José David Martín Guerrero (University of Valencia, Spain), Marcelino Martinez-Sober (University of Valencia, Spain), Jose Rafael Magdalena-Benedito (University of Valencia, Spain)and Antonio José Serrano López (University of Valencia, Spain)
DOI: 10.4018/978-1-60566-766-9.ch021
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Abstract
Stock breeding has been one of the most important sources of food and labour throughout human history. Every advance in this field has always led to important and beneficial impacts on human society. These innovations have mainly taken place in machines or genetics, but data analysis has been somewhat ignored. Most of the published works in data analysis use linear models, and there are few works in the literature that use non-linear methods for data processing in stock breeding where these methods have proven to obtain better results and performance than linear, classical methods. This chapter demonstrates the use of non-linear methods by presenting two practical applications: milk yield production in goats, and analysis of farming production systems.
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