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» Rank based variation operators for genetic algorithms
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CEC
2005
IEEE
14 years 1 months ago
A hybrid approach to parameter tuning in genetic algorithms
Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
Bo Yuan, Marcus Gallagher
CEC
2003
IEEE
13 years 11 months ago
A genetic algorithm for energy efficient device scheduling in real-time systems
Most embedded systemshave tightconstraints on power consumption because the amonnt of power available to these systems is limited due to the limitation ofbattery life. For this rea...
Lirong Tian, Tughrul Arslan
PR
1998
86views more  PR 1998»
13 years 7 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...
HIS
2004
13 years 9 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
FLAIRS
2006
13 years 9 months ago
Fuzzy Model Optimization Using Genetic Algorithm for Aircraft Engine Diagnosis
An accurate and up-to-date diagnostic model is critical for economic aircraft engine operation. However, for many commercial airline fleets, monitoring and diagnosing engine fault...
LiJie Yu, Daniel J. Cleary, Mark D. Osborn, Vrinda...