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» Multiple Layer Perceptron training using genetic algorithms
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IJON
2000
105views more  IJON 2000»
13 years 4 months ago
G-Prop: Global optimization of multilayer perceptrons using GAs
A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP...
Pedro A. Castillo Valdivieso, Juan J. Merelo Guerv...
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
13 years 9 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithm...
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S...
FLAIRS
2004
13 years 6 months ago
Indirect Encoding Evolutionary Learning Algorithm for the Multilayer Morphological Perceptron
This article describes an indirectly encoded evolutionary learning algorithm to train morphological neural networks. The indirect encoding method is an algorithm in which the trai...
Jorge L. Ortiz, Roberto Piñeiro
FLAIRS
2004
13 years 6 months ago
Hidden Layer Training via Hessian Matrix Information
The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights....
Changhua Yu, Michael T. Manry, Jiang Li