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GCB
1997
Springer
77views Biometrics» more  GCB 1997»
14 years 3 days ago
Statistics of large scale sequence searching
Motivation: Database search programs such as FASTA, BLAST or a rigorous Smith–Waterman algorithm produce lists of database entries, which are assumed to be related to the query....
Rainer Spang, Martin Vingron
EUROGP
2004
Springer
145views Optimization» more  EUROGP 2004»
14 years 1 months ago
Toward an Alternative Comparison between Different Genetic Programming Systems
In this paper, we use multi-objective techniques to compare different genetic programming systems, permitting our comparison to concentrate on the effect of representation and sepa...
Nguyen Xuan Hoai, Robert I. McKay, Daryl Essam, Hu...
ICARIS
2010
Springer
13 years 5 months ago
An Information-Theoretic Approach for Clonal Selection Algorithms
In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a lo...
Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone, ...
GECCO
2005
Springer
117views Optimization» more  GECCO 2005»
14 years 1 months ago
Directional self-learning of genetic algorithm
In order to overcome the low convergence speed and prematurity of classical genetic algorithm, an improved method named directional self-learning of genetic algorithm (DSLGA) is p...
Lin Cong, Yuheng Sha, Licheng Jiao, Fang Liu
AAAI
1998
13 years 9 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge