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» Genetic algorithms using low-discrepancy sequences
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CEC
2008
IEEE
10 years 7 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»
10 years 26 days 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
9 years 10 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»
10 years 2 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»
10 years 1 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
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