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» Removing the Genetics from the Standard Genetic Algorithm
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ENC
2004
IEEE
14 years 15 days ago
A Method Based on Genetic Algorithms and Fuzzy Logic to Induce Bayesian Networks
A method to induce bayesian networks from data to overcome some limitations of other learning algorithms is proposed. One of the main features of this method is a metric to evalua...
Manuel Martínez-Morales, Ramiro Garza-Dom&i...
MVA
2007
105views Computer Vision» more  MVA 2007»
13 years 10 months ago
Identifying Hand Gesture Images by Using Genetic Algorithms
A genetic algorithm (GA) is an optimization algorithm that simulates the hereditary phenomenon of natural life. Although GA has been applied to image processing, it has not been s...
Tetsuji Kobayashi, Norifumi Machida
CEC
2010
IEEE
13 years 10 months ago
A hybrid genetic algorithm and inver over approach for the travelling salesman problem
This paper proposes a two-phase hybrid approach for the travelling salesman problem (TSP). The first phase is based on a sequence based genetic algorithm (SBGA) with an embedded lo...
Shakeel Arshad, Shengxiang Yang
OL
2010
128views more  OL 2010»
13 years 7 months ago
A biased random-key genetic algorithm for road congestion minimization
One of the main goals in transportation planning is to achieve solutions for two classical problems, the traffic assignment and toll pricing problems. The traffic assignment proble...
Luciana S. Buriol, Michael J. Hirsch, Panos M. Par...
GECCO
2007
Springer
124views Optimization» more  GECCO 2007»
14 years 20 days ago
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
The Negative Slope Coefficient (nsc) is an empirical measure of problem hardness based on the analysis of offspring-fitness vs. parent-fitness scatterplots. The nsc has been teste...
Riccardo Poli, Leonardo Vanneschi