Memetic cooperative coevolution of Elman recurrent neural networks

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:	http://repository.usp.ac.fj/id/eprint/7540

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• Memetic cooperative coevolution of Elman recurrent neural networks. (deposited 30 Mar 2014 22:08)
  • Memetic cooperative coevolution of Elman recurrent neural networks. (deposited 21 Jul 2014 00:35) [Currently Displayed]

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