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» Removing the Genetics from the Standard Genetic Algorithm
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CEC
2005
IEEE
14 years 2 months ago
Linear genetic programming using a compressed genotype representation
This paper presents a modularization strategy for linear genetic programming (GP) based on a substring compression/substitution scheme. The purpose of this substitution scheme is t...
Johan Parent, Ann Nowé, Kris Steenhaut, Ann...
GECCO
2005
Springer
178views Optimization» more  GECCO 2005»
14 years 2 months ago
A co-evolutionary hybrid algorithm for multi-objective optimization of gene regulatory network models
In this paper, the parameters of a genetic network for rice flowering time control have been estimated using a multiobjective genetic algorithm approach. We have modified the rece...
Praveen Koduru, Sanjoy Das, Stephen Welch, Judith ...
ISNN
2007
Springer
14 years 2 months ago
Memetic Algorithms for Feature Selection on Microarray Data
In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods...
Zexuan Zhu, Yew-Soon Ong
GECCO
2003
Springer
415views Optimization» more  GECCO 2003»
14 years 1 months ago
Evolutionary Algorithms for Two Problems from the Calculus of Variations
Abstract. A brachistochrone is the path along which a weighted particle falls most quickly from one point to another, and a catenary is the smooth curve connecting two points whose...
Bryant A. Julstrom
NCA
2010
IEEE
13 years 7 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet