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Utilize este identificador para citar ou criar um link para este item: http://acervodigital.unesp.br/handle/11449/20318
Título: 
Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala
Autor(es): 
Instituição: 
Universidade Estadual Paulista (UNESP)
ISSN: 
1536-2442
Financiador: 
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo: 
Bionomic features of blowflies may be clarified and detailed by the deployment of appropriate modelling techniques such as artificial neural networks, which are mathematical tools widely applied to the resolution of complex biological problems. The principal aim of this work was to use three well-known neural networks, namely Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), and Adaptive Neural Network-Based Fuzzy Inference System (ANFIS), to ascertain whether these tools would be able to outperform a classical statistical method (multiple linear regression) in the prediction of the number of resultant adults (survivors) of experimental populations of Chrysomya megacephala (F.) (Diptera: Calliphoridae), based on initial larval density (number of larvae), amount of available food, and duration of immature stages. The coefficient of determination (R(2)) derived from the RBF was the lowest in the testing subset in relation to the other neural networks, even though its R2 in the training subset exhibited virtually a maximum value. The ANFIS model permitted the achievement of the best testing performance. Hence this model was deemed to be more effective in relation to MLP and RBF for predicting the number of survivors. All three networks outperformed the multiple linear regression, indicating that neural models could be taken as feasible techniques for predicting bionomic variables concerning the nutritional dynamics of blowflies.
Data de publicação: 
9-Jun-2010
Citação: 
Journal of Insect Science. Tucson: Univ Arizona, v. 10, p. 18, 2010.
Duração: 
18
Publicador: 
Univ Arizona
Palavras-chaves: 
  • insect bionomics
  • larval density
  • life-history
  • mass rearing
Fonte: 
http://www.insectscience.org/10.58/
Endereço permanente: 
http://hdl.handle.net/11449/20318
Direitos de acesso: 
Acesso aberto
Tipo: 
outro
Fonte completa:
http://repositorio.unesp.br/handle/11449/20318
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