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TEC
2012
234views Formal Methods» more  TEC 2012»
11 years 10 months ago
Cooperatively Coevolving Particle Swarms for Large Scale Optimization
—This paper presents a new cooperative coevolving particle swarm optimization (CCPSO) algorithm in an attempt to address the issue of scaling up particle swarm optimization (PSO)...
Xiaodong Li, Xin Yao
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
13 years 9 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
FLAIRS
2008
13 years 10 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
CEC
2008
IEEE
14 years 2 months ago
Auto-tuning fuzzy granulation for evolutionary optimization
—Much of the computational complexity in employing evolutionary algorithms as optimization tool is due to the fitness function evaluation that may either not exist or be computat...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
13 years 11 months ago
Designing safe, profitable automated stock trading agents using evolutionary algorithms
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...
Harish Subramanian, Subramanian Ramamoorthy, Peter...