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» Genetic algorithms using low-discrepancy sequences
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CEC
2008
IEEE
13 years 10 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...
RSA
2002
99views more  RSA 2002»
13 years 4 months ago
Distributed algorithms with dynamical random transitions
Given any measure-preserving dynamical system (Y, A , , T) and g Lp() , we study convergence of the sequence 1 n n k=1 g TSk , n 1 where Sk is a dynamic Zr -valued random w...
Nadine Guillotin-Plantard, René Schott
BIOCOMP
2010
13 years 1 months ago
Using the Genetic Code Wisdom for Recognizing Protein Coding Sequences
We have elaborated a new method of recognizing protein coding sequences in genomic sequences. The method is exploiting a specific way of genetic code degeneration and relations bet...
Pawel Blazej, Pawel Mackiewicz, Stanislaw Cebrat
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 5 months ago
Multiple sequence alignment using a GLOCSA guided genetic algorithm
This paper introduces GLOCSA as a new scoring function to rate multiple sequence alignments. It is intended to be simple, considering the whole alignment at once and reflecting t...
Edgar David Arenas-Díaz, Helga Ochoterena-B...
BMCBI
2005
102views more  BMCBI 2005»
13 years 4 months ago
Genomic multiple sequence alignments: refinement using a genetic algorithm
Background: Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics
Chunlin Wang, Elliot J. Lefkowitz