Use este identificador para citar ou linkar para este item: http://repositoriosenaiba.fieb.org.br/handle/fieb/588
Título: A model for improving the learning curves of artificial neural network
Título(s) alternativo(s): Plos One
Autor(es): Monteiro, Roberto L. S.
Carneiro, Tereza Kelly G.
Fontoura, José Roberto A.
Silva, Valéria L. da
Moret, Marcelo A.
Pereira, Hernane Borges de Barros
Palavras-chave: Artificial neural networks
Data do documento: Fev-2016
Citação: MONTEIRO, Roberto L. S. et al. A model for improving the learning curves of artificial neural networks. Plos One, China, 2016.
Resumo: In this article, the performance of a hybrid artificial neural network (i.e. scale-free and smallworld) was analyzed and its learning curve compared to three other topologies: random, scale-free and small-world, as well as to the chemotaxis neural network of the nematode Caenorhabditis Elegans. One hundred equivalent networks (same number of vertices and average degree) for each topology were generated and each was trained for one thousand epochs. After comparing the mean learning curves of each network topology with the C. elegans neural network, we found that the networks that exhibited preferential attachment exhibited the best learning curves.
URI: http://repositoriosenaiba.fieb.org.br/handle/fieb/588
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