USP Electronic Research Repository

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

This is the latest version of this item.

[img]
Preview
PDF - Accepted Version
Download (659Kb) | Preview

    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 12:35
    Last Modified: 05 May 2016 09:40
    URI: http://repository.usp.ac.fj/id/eprint/7540

    Available Versions of this Item

    UNSPECIFIED

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...