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CORR
2010
Springer
427views Education» more  CORR 2010»
13 years 5 months ago
A Comparison between Memetic algorithm and Genetic algorithm for the cryptanalysis of Simplified Data Encryption Standard algori
Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent charact...
Poonam Garg
GECCO
2000
Springer
13 years 11 months ago
Modeling GA Performance for Control Parameter Optimization
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
Vincent A. Cicirello, Stephen F. Smith
EUSFLAT
2009
152views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Learning Fuzzy Rule Based Classifier in High Performance Computing Environment
-- An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high ...
Vinicius da F. Vieira, Alexandre Evsukoff, Beatriz...
ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
14 years 1 months ago
Dejong Function Optimization by Means of a Parallel Approach to Fuzzified Genetic Algorithm
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
Ebrahim Bagheri, Hossein Deldari
AIR
1998
103views more  AIR 1998»
13 years 7 months ago
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Abstract. Genetic algorithms play a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc...
Francisco Herrera, Manuel Lozano, José L. V...