12 search results - page 1 / 3 » Comparing neural networks and Kriging for fitness approximat... |
CEC
2003
IEEE
13 years 10 months ago
2003
IEEE
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...
GECCO
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. In many real-world applications of evolutionary computation, it is essential to reduce the number of fitness evaluations. To this end, computationally efficient models c...
IJCNN
2006
IEEE
13 years 11 months ago
2006
IEEE
— The optimization of classification systems is often confronted by the solution over-fit problem. Solution over-fit occurs when the optimized classifier memorizes the traini...
NC
1998
13 years 6 months ago
1998
In this paper a new approach for approximation problems involving only few input and output parameters is presented and compared to traditional Backpropagation Neural Networks (BP...
ARTMED
2002
13 years 4 months ago
2002
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...