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» On the practical genetic algorithms
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CIDM
2007
IEEE
16 years 1 months ago
K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
Eli Faulkner
BMCBI
2007
108views more  BMCBI 2007»
15 years 6 months ago
Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants
Background: Single nucleotide polymorphisms (SNPs) and genes that exhibit presence/absence variation have provided informative marker sets for bacterial and viral genotyping. Iden...
Erin P. Price, John Inman-Bamber, Venugopal Thiruv...
AINA
2009
IEEE
16 years 1 months ago
Reliability-Driven Reputation Based Scheduling for Public-Resource Computing Using GA
— For an application in public-resource computing environments, providing reliable scheduling based on resource reliability evaluation is becoming increasingly important. Most ex...
Xiaofeng Wang, Chee Shin Yeo, Rajkumar Buyya, Jins...
GECCO
2007
Springer
154views Optimization» more  GECCO 2007»
16 years 25 days ago
A novel ab-initio genetic-based approach for protein folding prediction
In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary str...
Sergio Raul Duarte Torres, David Camilo Becerra Ro...
PPSN
2000
Springer
15 years 10 months ago
Practical Implications of New Results in Conservation of Optimizer Performance
Abstract. Three theoretical perspectives upon conservation of performance in function optimization are outlined. In terms of statistical information, performance is conserved when ...
Thomas M. English