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» Convergence Models of Genetic Algorithm Selection Schemes
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GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
14 years 1 months ago
A hardware pipeline for function optimization using genetic algorithms
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
Malay Kumar Pakhira, Rajat K. De
AEI
1999
110views more  AEI 1999»
13 years 7 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
CORR
2004
Springer
92views Education» more  CORR 2004»
13 years 7 months ago
Tournament versus Fitness Uniform Selection
1 In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely...
Shane Legg, Marcus Hutter, Akshat Kumar
GECCO
2006
Springer
130views Optimization» more  GECCO 2006»
13 years 11 months ago
An efficient multi-objective evolutionary algorithm with steady-state replacement model
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...
Dipti Srinivasan, Lily Rachmawati
ACCV
1998
Springer
13 years 11 months ago
Shape Modeling from Multiple View Images Using GAs
Shape modeling is a very important issue for many study, for example, object recognition for robot vision, virtual environment construction, and so on. In this paper, a new method...
Satoshi Kirihara, Hideo Saito