135 search results - page 3 / 27 » Solving the Ill-Conditioning in Neural Network Learning |
VISUALIZATION
2005
IEEE
13 years 12 months ago
2005
IEEE
Arti cial neural networks are computer software or hardware models inspired by the structure and behavior of neurons in the human nervous system. As a powerful learning tool, incr...
CIMCA
2005
IEEE
13 years 12 months ago
2005
IEEE
Hybrid set of optimally trained feed-forward, Hopfield and Elman neural networks were used as computational tools and were applied to immunoinformatics. These neural networks ena...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
GECCO
2010
Springer
13 years 11 months ago
2010
Springer
Neuro-evolution and computational neuroscience are two scientific domains that produce surprisingly different artificial neural networks. Inspired by the “toolbox” used by ...
TNN
2010
2010
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
13 years 29 days ago
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...