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ESANN
2001
14 years 11 months ago
Motor control and movement optimization learned by combining auto-imitative and genetic algorithms
In sensorimotor behaviour often a great movement execution variability is combined with a relatively low error in reaching the intended goal. This phenomenon can especially be obse...
Karl-Theodor Kalveram, Ulrich Nakte
PR
1998
86views more  PR 1998»
14 years 9 months ago
Optimizing the cost matrix for approximate string matching using genetic algorithms
This paper describes a method for optimizing the cost matrix of any approximate string matching algorithm based on the Levenshtein distance. The method, which uses genetic algorit...
Marc Parizeau, Nadia Ghazzali, Jean-Françoi...
87
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GECCO
2003
Springer
114views Optimization» more  GECCO 2003»
15 years 3 months ago
Genetic Algorithm for Supply Planning Optimization under Uncertain Demand
Supply planning optimization is one of the most important issues for manufacturers and distributors. Supply is planned to meet the future demand. Under the uncertainty involved in ...
Masaru Tezuka, Masahiro Hiji
GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
15 years 3 months ago
A multi-objective genetic algorithm for robust design optimization
Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...
Mian Li, Shapour Azarm, Vikrant Aute
GECCO
2003
Springer
171views Optimization» more  GECCO 2003»
15 years 3 months ago
Genetic Algorithm Optimized Feature Transformation - A Comparison with Different Classifiers
When using a Genetic Algorithm (GA) to optimize the feature space of pattern classification problems, the performance improvement is not only determined by the data set used, but a...
Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huan...