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» On the generality of parameter tuning in evolutionary planni...
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 6 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
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 9 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
13 years 11 months ago
An online implementable differential evolution tuned optimal guidance law
This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engag...
Raghunathan Thangavelu, S. Pradeep
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
13 years 12 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
13 years 10 months ago
Using performance fronts for parameter setting of stochastic metaheuristics
In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called “performance fronts” pres...
Johann Dréo