A Model for Improving the Learning Curves of Artificial Neural Networks |
| |
Authors: | Roberto L S Monteiro Tereza Kelly G Carneiro José Roberto A Fontoura Valéria L da Silva Marcelo A Moret Hernane Borges de Barros Pereira |
| |
Institution: | 1. Programa de Modelagem Computational, SENAI CIMATEC, Av. Orlando Gomes 1845, Salvador, 41.650-010, Brazil.; 2. Universidade do Estado da Bahia, Salvador, Brasil.; 3. Universidade Estadual de Ciências da Saúde de Alagoas, Maceió, Brazil.; Beihang University, CHINA, |
| |
Abstract: | 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. |
| |
Keywords: | |
|
|