99 search results - page 10 / 20 » Evolving Crossover Operators for Function Optimization |
SBRN
2000
IEEE
13 years 12 months ago
2000
IEEE
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
PPSN
2004
Springer
14 years 25 days ago
2004
Springer
This article describes a new model of probability density function and its use in estimation of distribution algorithms. The new model, the distribution tree, has interesting prope...
GECCO
2000
Springer
13 years 11 months ago
2000
Springer
We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical gene...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
This paper presents a novel evolutionary approach to solve numerical optimization problems, called Adaptive Evolution (AEv). AEv is a new micro-population-like technique because i...
GECCO
2009
Springer
14 years 2 months ago
2009
Springer
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...