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» The evolutionary forest algorithm
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114
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SASO
2009
IEEE
15 years 7 months ago
Evolution of Probabilistic Consensus in Digital Organisms
—The complexity of distributed computing systems and their increasing interaction with the physical world impose challenging requirements in terms of adaptation, robustness, and ...
David B. Knoester, Philip K. McKinley
88
Voted
ACCV
2009
Springer
15 years 7 months ago
A Smarter Particle Filter
Particle filtering is an effective sequential Monte Carlo approach to solve the recursive Bayesian filtering problem in non-linear and non-Gaussian systems. The algorithm is base...
Xiaoqin Zhang, Weiming Hu, Steve J. Maybank
106
Voted
CEC
2007
IEEE
15 years 7 months ago
Parameter calibration using meta-algorithms
— Calibrating an evolutionary algorithm (EA) means finding the right values of algorithm parameters for a given problem. This issue is highly relevant, because it has a high imp...
W. A. de Landgraaf, A. E. Eiben, Volker Nannen
115
Voted
GECCO
2007
Springer
211views Optimization» more  GECCO 2007»
15 years 6 months ago
Multi-objective univariate marginal distribution optimisation of mixed analogue-digital signal circuits
Design for specific customer service plays a crucial role for the majority of the market in modern electronics. However, adaptability to an individual customer results in increasi...
Lyudmila Zinchenko, Matthias Radecker, Fabio Bisog...
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
15 years 6 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen