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GECCO
2005
Springer
288views Optimization» more  GECCO 2005»
16 years 13 days ago
A comparison study between genetic algorithms and bayesian optimize algorithms by novel indices
Genetic Algorithms (GAs) are a search and optimization technique based on the mechanism of evolution. Recently, another sort of population-based optimization method called Estimat...
Naoki Mori, Masayuki Takeda, Keinosuke Matsumoto
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
16 years 13 days ago
A comparison of evolutionary algorithms for system-level diagnosis
The size and complexity of systems based on multiple processing units demand techniques for the automatic diagnosis of their state. System-level diagnosis consists in determining ...
Bogdan Tomoyuki Nassu, Elias Procópio Duart...
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
16 years 13 days ago
Genetic programming: parametric analysis of structure altering mutation techniques
We hypothesize that the relationship between parameter settings, speci cally parameters controlling mutation, and performance is non-linear in genetic programs. Genetic programmin...
Alan Piszcz, Terence Soule
162
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GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
16 years 13 days ago
Real-coded crossover as a role of kernel density estimation
This paper presents a kernel density estimation method by means of real-coded crossovers. Estimation of density algorithms (EDAs) are evolutionary optimization techniques, which d...
Jun Sakuma, Shigenobu Kobayashi
GECCO
2005
Springer
121views Optimization» more  GECCO 2005»
16 years 13 days ago
An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection
This paper introduces hyper-ellipsoids as an improvement to hyper-spheres as intrusion detectors in a negative selection problem within an artificial immune system. Since hyper-s...
Joseph M. Shapiro, Gary B. Lamont, Gilbert L. Pete...