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01.08.2014 | Methodologies and Application

Memetic cooperative coevolution of Elman recurrent neural networks

verfasst von: Rohitash Chandra

Erschienen in: Soft Computing | Ausgabe 8/2014

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Abstract

Cooperative coevolution decomposes an optimisation 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.

Vorheriger Artikel Metaheuristic algorithms for the design of multiplier-less non-uniform filter banks based on frequency response masking

Nächster Artikel A generalized computing paradigm based on artificial dynamic models for mathematical programming

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Titel: Memetic cooperative coevolution of Elman recurrent neural networks
verfasst von: Rohitash Chandra
Publikationsdatum: 01.08.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 8/2014
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1160-1

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