Chandra, Rohitash (2014) Memetic cooperative coevolution of Elman recurrent neural networks. Soft Computing, 18 (8). pp. 1549-1559. ISSN 1432-7643
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Abstract
Cooperative coevolution decomposes an optimi-
sation problem into subcomponents and collectively solves
them using evolutionary algorithms. Memetic algorithms
provides enhancement to evolutionary algorithms with local
search. Recently, the incorporation of local search into a
memetic cooperative coevolution method has shown to be
efficient for training feedforward networks on pattern classification problems. This paper applies the memetic cooperative coevolution method for training recurrent neural networks on grammatical inference problems. The results show
that the proposed method achieves better performance in
terms of optimisation time and robustness.
| Item Type: | Journal Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences |
| Depositing User: | Rohitash Chandra |
| Date Deposited: | 21 Jul 2014 00:35 |
| Last Modified: | 04 May 2016 21:40 |
| URI: | https://repository.usp.ac.fj/id/eprint/7540 |
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