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GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
14 years 1 months ago
Markov chain models of bare-bones particle swarm optimizers
We apply a novel theoretical approach to better understand the behaviour of different types of bare-bones PSOs. It avoids many common but unrealistic assumptions often used in an...
Riccardo Poli, William B. Langdon
PRL
2007
180views more  PRL 2007»
13 years 7 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...
GECCO
2005
Springer
112views Optimization» more  GECCO 2005»
14 years 28 days ago
Two improved differential evolution schemes for faster global search
Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of D...
Swagatam Das, Amit Konar, Uday Kumar Chakraborty
JUCS
2008
159views more  JUCS 2008»
13 years 7 months ago
Two Step Swarm Intelligence to Solve the Feature Selection Problem
: In this paper we propose a new approach to Swarm Intelligence called Two-Step Swarm Intelligence. The basic idea is to split the heuristic search performed by agents into two sta...
Yudel Gómez, Rafael Bello, Amilkar Puris, M...
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 1 months ago
Two-level of nondominated solutions approach to multiobjective particle swarm optimization
In multiobjective particle swarm optimization (MOPSO) methods, selecting the local best and the global best for each particle of the population has a great impact on the convergen...
M. A. Abido