Summary
International Symposium on Nonlinear Theory and Its Applications
2022
Session Number:C3L-C
Session:
Number:C3L-C-01
Learning a Simple Multilayer Perceptron with PSO
Riku Takato , Kenya Jin'no,
pp.470-473
Publication Date:12/12/2022
Online ISSN:2188-5079
Summary:
In this article, we attempt to learn the parameters of a multi-layer perceptron (MLP) using the particle swarm optimization (PSO) method which is one of the approximate solution methods for optimization problems without using the derivative information of the objective function. We use gradient method and PSO to learn to classify a linearly inseparable data set with an MLP in the middle layer with a small number of neurons. As a result, we experimentally confirm that PSO outperforms gradient-based learning.