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CIBCB
2005
IEEE
14 years 2 months ago
Feature Selection for Microarray Data Using Least Squares SVM and Particle Swarm Optimization
Feature selection is an important preprocessing technique for many pattern recognition problems. When the number of features is very large while the number of samples is relatively...
E. Ke Tang, Ponnuthurai N. Suganthan, Xin Yao
GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
14 years 3 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
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
14 years 3 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
GECCO
2007
Springer
314views Optimization» more  GECCO 2007»
14 years 3 months ago
Variable selection for wind power prediction using particle swarm optimization
Wind energy has an increasing influence on the energy supply in many countries, but in contrast to conventional power plants it is a fluctuating energy source. For its integration...
René Jursa
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
14 years 2 months ago
Better Spread and Convergence: Particle Swarm Multiobjective Optimization Using the Maximin Fitness Function
Maximin strategy has its origin in game theory, but it can be adopted for effective multiobjective optimization. This paper proposes a particle swarm multiobjective optimiser, max...
Xiaodong Li