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» Combining mutation operators in evolutionary programming
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EUROGP
2006
Springer
138views Optimization» more  EUROGP 2006»
13 years 10 months ago
Evolving Crossover Operators for Function Optimization
Abstract. A new model for evolving crossover operators for evolutionary function optimization is proposed in this paper. The model is a hybrid technique that combines a Genetic Pro...
Laura Diosan, Mihai Oltean
PRL
2002
128views more  PRL 2002»
13 years 6 months ago
Dynamic flies: a new pattern recognition tool applied to stereo sequence processing
The "fly algorithm" is a fast artificial evolution-based technique devised for the exploration of parameter space in pattern recognition applications. In the application...
Jean Louchet, Maud Guyon, Marie-Jeanne Lesot, Amin...
RECOMB
2002
Springer
14 years 7 months ago
Comparison of minisatellites
In the class of repeated sequences that occur in DNA, minisatellites have been found polymorphic and became useful tools in genetic mapping and forensic studies. They consist of a...
Eric Rivals, Sèverine Bérard
CCE
2010
13 years 4 months ago
Combined mass and energy integration in process design at the example of membrane-based gas separation systems
This paper presents an approach for combined mass and energy integration in process synthesis and illustrates it at the thermochemical production of crude synthetic natural gas (S...
Martin Gassner, François Maréchal
SIGADA
2004
Springer
14 years 9 days ago
Comparative analysis of genetic algorithm implementations
Genetic Algorithms provide computational procedures that are modeled on natural genetic system mechanics, whereby a coded solution is “evolved” from a set of potential solutio...
Robert Soricone, Melvin Neville