| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6874638 | Journal of Computational Science | 2012 | 10 Pages |
Abstract
⺠We train a neural network by using particle swarm optimization with a differential evolutionary algorithm. ⺠We examine the changes obtained by this method and the classic one. ⺠Once several networks are trained, we can find the most suitable to solve a complex problem by using grammatical swarm.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Luis Fernando de Mingo López, Nuria Gómez Blas, Alberto Arteta,