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» An evolutionary method for complex-process optimization
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
15 years 1 months ago
A hybrid method for tuning neural network for time series forecasting
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
Aranildo Rodrigues Lima Junior, Tiago Alessandro E...
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 1 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb
CEC
2009
IEEE
15 years 7 months ago
Mining an optimal prototype from a periodic time series: An evolutionary computation-based approach
— The mining of meaningful shapes of time series is done widely in order to find shapes that can be used, for example, in classification problems or in summarizing signals. Nor...
Pekka Siirtola, Perttu Laurinen, Juha Röning
EMO
2001
Springer
150views Optimization» more  EMO 2001»
15 years 4 months ago
On the Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization
This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
Marco Laumanns, Eckart Zitzler, Lothar Thiele
CEC
2003
IEEE
15 years 5 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
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...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...