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» Data Mining for Genetics: A Genetic Algorithm Approach
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IPPS
1999
IEEE
14 years 1 months ago
Distributed Scheduling with Decomposed Optimization Criterion: Genetic Programming Approach
Abstract. A new approach to develop parallel and distributed scheduling algorithms for multiprocessor systems is proposed. Its main innovation lies in evolving a decomposition of t...
Franciszek Seredynski, Jacek Koronacki, Cezary Z. ...
APBC
2004
164views Bioinformatics» more  APBC 2004»
13 years 10 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo
BMCBI
2008
214views more  BMCBI 2008»
13 years 7 months ago
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Jukka Corander, Pekka Marttinen, Jukka Siré...
EUROGP
2008
Springer
137views Optimization» more  EUROGP 2008»
13 years 11 months ago
A Comparison of Cartesian Genetic Programming and Linear Genetic Programming
Two prominent genetic programming approaches are the graph-based Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP). Recently, a formal algorithm for construc...
Garnett Carl Wilson, Wolfgang Banzhaf
IJISTA
2007
119views more  IJISTA 2007»
13 years 9 months ago
Online modelling based on Genetic Programming
: Genetic Programming (GP), a heuristic optimisation technique based on the theory of Genetic Algorithms (GAs), is a method successfully used to identify non-linear model structure...
Stephan M. Winkler, Hajrudin Efendic, Luigi del Re...