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A Model for Improving the Learning Curves of Artificial Neural Networks

2016; Public Library of Science; Volume: 11; Issue: 2 Linguagem: Inglês

10.1371/journal.pone.0149874

1932-6203

Roberto Luiz Souza Monteiro, Tereza Kelly Gomes Carneiro, José Roberto A. Fontoura, Valéria Loureiro da Silva, Marcelo A. Moret, Hernane Borges de Barros Pereira,

Genetics, Aging, and Longevity in Model Organisms

In this article, the performance of a hybrid artificial neural network (i.e. scale-free and small-world) 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.