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NN
2007
Springer
267views Neural Networks» more  NN 2007»
13 years 8 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
WSC
2008
13 years 10 months ago
Simulation optimization for industrial scheduling using hybrid genetic representation
Simulation modeling has the capability to represent complex real-world systems in details and therefore it is suitable to develop simulation models for generating detailed operati...
Marcus Andersson, Amos Ng, Henrik Grimm
AI
1998
Springer
13 years 8 months ago
GAS, A Concept on Modeling Species in Genetic Algorithms
This paper introduces a niching technique called GAS (S stands for species) which dynamically creates a subpopulation structure (taxonomic chart) using a radius function instead of...
Márk Jelasity, József Dombi
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
14 years 3 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
PPSN
1998
Springer
14 years 21 days ago
Restart Scheduling for Genetic Algorithms
Abstract. In order to escape from local optima, it is standard practice to periodically restart a genetic algorithm according to some restart criteria/policy. This paper addresses ...
Alex S. Fukunaga