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Neural Computing and Applications

, Volume 16, Issue 3, pp 207–208 | Cite as

Hybrid artificial neural network

  • Nadia Nedjah
  • Ajith Abraham
  • Luiza M. Mourelle
Editorial

Artificial neural networks (ANNs) or simply neural networks (NNs) are now a consolidated technique in computational intelligence. They consist of interconnected cells, called neurons, and simulate the behavior of the biological neural network in a human brain. For that purpose, ANNs use a statistical non-linear computational model. Neural networks are generally used to model complex relationships between inputs and outputs or to classify data finding common patterns.

Computationally speaking, the model behind neural networks needs heavy efforts and therefore researchers are always trying to find a way to perform the neural process efficiently. One valid attempt to improve this process consists of hybridizing other techniques of computational intelligence with neural networks. This special issue is devoted to research papers on hybrid artificial neural network. Evolutionary computation, fuzzy logic, ant colony as well as hardware implementation are considered in the articles of this...

Keywords

Little Square Support Vector Machine Neural Network Training Imbalanced Data Imbalance Ratio Hybrid Classifier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag London Limited 2007

Authors and Affiliations

  • Nadia Nedjah
    • 1
  • Ajith Abraham
    • 1
  • Luiza M. Mourelle
    • 1
  1. 1.Rio de JaneiroBrazil

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