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» Modified genetic algorithm for nonlinear data reconciliation
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PRL
2006
130views more  PRL 2006»
13 years 7 months ago
Efficient huge-scale feature selection with speciated genetic algorithm
With increasing interest in bioinformatics, sophisticated tools are required to efficiently analyze gene information. The classification of gene expression profiles is crucial in ...
Jin-Hyuk Hong, Sung-Bae Cho
TEC
2002
161views more  TEC 2002»
13 years 7 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
GECCO
2008
Springer
174views Optimization» more  GECCO 2008»
13 years 8 months ago
Mask functions for the symbolic modeling of epistasis using genetic programming
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
ICPR
2002
IEEE
14 years 8 months ago
Radial Projections for Non-Linear Feature Extraction
In this work, two new techniques for non-linear feature extraction are presented. In these techniques, new features are obtained as radial projections of the original measurements...
Alberto J. Pérez Jiménez, Juan Carlo...
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
14 years 1 months ago
A NSGA-II, web-enabled, parallel optimization framework for NLP and MINLP
Engineering design increasingly uses computer simulation models coupled with optimization algorithms to find the best design that meets the customer constraints within a time con...
David J. Powell, Joel K. Hollingsworth