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GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
13 years 11 months ago
Breeding swarms: a new approach to recurrent neural network training
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
Matthew Settles, Paul Nathan, Terence Soule
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
13 years 11 months ago
A pareto archive evolutionary strategy based radial basis function neural network training algorithm for failure rate prediction
This paper outlines a radial basis function neural network approach to predict the failures in overhead distribution lines of power delivery systems. The RBF networks are trained ...
Grant Cochenour, Jerad Simon, Sanjoy Das, Anil Pah...
IJCAI
1989
13 years 6 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
IJON
2007
118views more  IJON 2007»
13 years 5 months ago
Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm
To predict the 100 missing values from a time series of 5000 data points, given for the IJCNN 2004 time series prediction competition, recurrent neural networks (RNNs) are trained...
Xindi Cai, Nian Zhang, Ganesh K. Venayagamoorthy, ...
ACMSE
2008
ACM
13 years 7 months ago
Training approaches in neural enhancement for multiobjective optimization
In previous work, a neural network was used to increase the number of solutions found by an evolutionary multiobjective optimization algorithm. In this paper, various approaches a...
Aaron Garrett, Gerry V. Dozier