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» Neural networks: Algorithms and applications
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CEC
2003
IEEE
15 years 11 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
Neural networks and the Kriging method are compared for constructing £tness approximation models in evolutionary optimization algorithms. The two models are applied in an identica...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...
198
Voted
APBC
2004
166views Bioinformatics» more  APBC 2004»
15 years 7 months ago
A Novel Method for Protein Subcellular Localization Based on Boosting and Probabilistic Neural Network.
Subcellular localization is a key functional characteristic of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is needed for ...
Jian Guo, Yuanlie Lin, Zhirong Sun
ASC
2004
15 years 6 months ago
Extracting rules from trained neural network using GA for managing E-business
Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to ...
Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami
TNN
2010
171views Management» more  TNN 2010»
15 years 24 days ago
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
Juan Carlos Fernández Caballero, Francisco ...
AAAI
1994
15 years 7 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen