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SBRN
2000
IEEE
14 years 2 months ago
Evolutionary Optimization of RBF Networks
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
Estefane G. M. de Lacerda, Teresa Bernarda Ludermi...
GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
14 years 3 months ago
Distributed genetic algorithm for subtraction radiography
Digital subtraction is a promising technique used in radiographic studies of periapical lesions and other dental disorders for which the treatment must be evaluated over time. Thi...
Gabriel Mañana, Fabio A. González, E...
GECCO
2004
Springer
14 years 3 months ago
Virtual Ramping of Genetic Programming Populations
Abstract. Genetic Programming often uses excessive computational resources because the population size and the maximum number of generations per run are not optimized. We have deve...
Thomas Fernandez
HAIS
2009
Springer
14 years 2 months ago
Automatic Clustering Using a Synergy of Genetic Algorithm and Multi-objective Differential Evolution
— This paper applies the Differential Evolution (DE) and Genetic Algorithm (GA) to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It com...
Debarati Kundu, Kaushik Suresh, Sayan Ghosh, Swaga...
EUROGP
2001
Springer
103views Optimization» more  EUROGP 2001»
14 years 2 months ago
Computational Complexity, Genetic Programming, and Implications
Recent theory work has shown that a Genetic Program (GP) used to produce programs may have output that is bounded above by the GP itself [l]. This paper presents proofs that show t...
Bart Rylander, Terence Soule, James A. Foster