Hybrid artificial neural networks: models, algorithms and data

Authors:
P. A. Gutiérrez;C. Hervás-Martínez
Affiliations:
Department of Computer Science and Numerical Analysis, University of Córdoba, Spain;Department of Computer Science and Numerical Analysis, University of Córdoba, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. ANNs are one of the three main components of computational intelligence and, as such, they have been often hybridized from different perspectives. In this paper, a review of some of the main contributions for hybrid ANNs is given, considering three points of views: models, algorithms and data.