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Automated early detection of drops in commercial egg production using neural networks.
Ramírez-Morales, I; Fernández-Blanco, E; Rivero, D; Pazos, A.
Afiliação
  • Ramírez-Morales I; a Universidad Técnica de Machala , Faculty of Agricultural & Livestock Sciences , Machala , Ecuador.
  • Fernández-Blanco E; b Universidade A Coruña , Department of Computer Science , A Coruña , España.
  • Rivero D; b Universidade A Coruña , Department of Computer Science , A Coruña , España.
  • Pazos A; b Universidade A Coruña , Department of Computer Science , A Coruña , España.
Br Poult Sci ; 58(6): 739-747, 2017 Dec.
Article em En | MEDLINE | ID: mdl-28929797
ABSTRACT
1. The purpose of this work was to support decision-making in poultry farms by performing automatic early detection of anomalies in egg production. 2. Unprocessed data were collected from a commercial egg farm on a daily basis over 7 years. Records from a total of 24 flocks, each with approximately 20 000 laying hens, were studied. 3. Other similar works have required a prior feature extraction by a poultry expert, and this method is dependent on time and expert knowledge. 4. The present approach reduces the dependency on time and expert knowledge because of the automatic selection of relevant features and the use of artificial neural networks capable of cost-sensitive learning. 5. The optimum configuration of features and parameters in the proposed model was evaluated on unseen test data obtained by a repeated cross-validation technique. 6. The accuracy, sensitivity, specificity and positive predictive value are presented and discussed at 5 forecasting intervals. The accuracy of the proposed model was 0.9896 for the day before a problem occurs.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Óvulo / Galinhas / Redes Neurais de Computação / Criação de Animais Domésticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Animals Idioma: En Revista: Br Poult Sci Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Equador

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Óvulo / Galinhas / Redes Neurais de Computação / Criação de Animais Domésticos Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Animals Idioma: En Revista: Br Poult Sci Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Equador