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» Training Neural Networks with GA Hybrid Algorithms
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CEC
2007
IEEE
15 years 8 months ago
NEMO: neural enhancement for multiobjective optimization
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
Aaron Garrett, Gerry V. Dozier, Kalyanmoy Deb
120
Voted
INFORMATICALT
2000
178views more  INFORMATICALT 2000»
15 years 1 months ago
Neural Network for Color Constancy
Abstract. Color constancy is the perceived stability of the color of objects under different illuminants. Four-layer neural network for color constancy has been developed. It has s...
Rytis Stanikunas, Henrikas Vaitkevicius
98
Voted
IJCNN
2006
IEEE
15 years 8 months ago
High-speed Bi-directional Function Approximation using Plausible Neural Networks
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen
ANSS
1998
IEEE
15 years 6 months ago
On Interval Weighted Three-Layer Neural Networks
In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
Mohsen Beheshti, Ali Berrached, André de Ko...
APIN
2005
92views more  APIN 2005»
15 years 1 months ago
A Hybrid Neural-Genetic Algorithm for the Frequency Assignment Problem in Satellite Communications
A hybrid Neural-Genetic algorithm (NG) is presented for the frequency assignment problem in satellite communications (FAPSC). The goal of this problem is minimizing the cochannel i...
Sancho Salcedo-Sanz, Carlos Bousoño-Calz&oa...