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» Particle Swarm Optimization Using Adaptive Mutation
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APIN
2000
120views more  APIN 2000»
14 years 9 months ago
Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Francisco Herrera, Manuel Lozano
WCNC
2008
IEEE
15 years 3 months ago
Using Swarm Intelligence and Bayesian Inference for Aircraft Interrogation
: Sensor management deals with the efficient resource allocation to meet mission objectives of the application, air traffic control. A schedule for the sensors is constructed, whic...
Ganapathi Kamath, Xiang Ye, Lisa Ann Osadciw
GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
14 years 10 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck
GECCO
2009
Springer
115views Optimization» more  GECCO 2009»
15 years 2 months ago
Rapid prototyping using evolutionary approaches: part 2
In this paper we extend the work done in [5], where authors have proposed a evolutionary multi-objective approach to Rapid Prototyping (RP), to decipher optimal build orientation ...
Nikhil Padhye, Subodh Kalia
ICASSP
2011
IEEE
14 years 1 months ago
Optimal SIR algorithm vs. fully adapted auxiliary particle filter: A matter of conditional independence
Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse the Sampling Importanc...
François Desbouvries, Yohan Petetin, Emmanu...