Hybrid Artificial Neural Networks: Models, Algorithms and Data
نویسندگان
چکیده
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.
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