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» A hybrid approach to parameter tuning in genetic algorithms
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CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 7 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
ICPR
2008
IEEE
14 years 2 months ago
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training
Hidden Markov Model (HMM) is the dominant technology in speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. The Ba...
Fengqin Yang, Changhai Zhang, Tieli Sun
JACIII
2007
103views more  JACIII 2007»
13 years 7 months ago
Dynamically Adjusting Migration Rates for Multi-Population Genetic Algorithms
In this paper, the issue of adapting migration parameters for MGAs is investigated. We examine, in particular, the effect of adapting the migration rates on the performance and so...
Tzung-Pei Hong, Wen-Yang Lin, Shu-Min Liu, Jiann-H...
IPPS
1999
IEEE
13 years 12 months ago
A Parallel Hybrid Evolutionary Metaheuristic for the Period Vehicle Routing Problem
Abstract. This paper presents a Parallel Hybrid Evolutionary Metaheuristic for the Period Vehicle Routing Problem PVRP. The PRVP generalizes the classical Vehicle Routing Problem b...
Dalessandro Soares Vianna, Luiz Satoru Ochi, L&uac...
BIOSYSTEMS
2008
129views more  BIOSYSTEMS 2008»
13 years 7 months ago
Reconstruction of DNA sequences using genetic algorithms and cellular automata: Towards mutation prediction?
Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not ...
Ch. Mizas, Georgios Ch. Sirakoulis, Vasilios A. Ma...