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» Morphing methods in evolutionary design optimization
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EVOW
2010
Springer
14 years 5 months ago
Parameter Tuning of Evolutionary Algorithms: Generalist vs. Specialist
Abstract. Finding appropriate parameter values for Evolutionary Algorithms (EAs) is one of the persistent challenges of Evolutionary Computing. In recent publications we showed how...
Selmar K. Smit, A. E. Eiben
APIN
1998
139views more  APIN 1998»
13 years 10 months ago
Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact ...
Sung-Bae Cho, Katsunori Shimohara
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
14 years 4 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
CEC
2005
IEEE
14 years 4 months ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 5 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels