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GECCO
2005
Springer
157views Optimization» more  GECCO 2005»
15 years 7 months ago
Simple addition of ranking method for constrained optimization in evolutionary algorithms
During the optimization of a constrained problem using evolutionary algorithms (EAs), an individual in the population can be described using three important properties, i.e., obje...
Pei Yee Ho, Kazuyuki Shimizu
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
15 years 7 months ago
Learning, anticipation and time-deception in evolutionary online dynamic optimization
In this paper we focus on an important source of problem– difficulty in (online) dynamic optimization problems that has so far received significantly less attention than the tr...
Peter A. N. Bosman
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
15 years 7 months ago
Morphing methods in evolutionary design optimization
Design optimization is a well established application field of evolutionary computation. However, standard recombination operators acting on the genotypic representation of the d...
Michael Nashvili, Markus Olhofer, Bernhard Sendhof...
DMIN
2006
126views Data Mining» more  DMIN 2006»
15 years 3 months ago
Comparison and Analysis of Mutation-based Evolutionary Algorithms for ANN Parameters Optimization
Mutation-based Evolutionary Algorithms, also known as Evolutionary Programming (EP) are commonly applied to Artificial Neural Networks (ANN) parameters optimization. This paper pre...
Kristina Davoian, Alexander Reichel, Wolfram-Manfr...
HIS
2008
15 years 3 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera