Code formation
genealgo
Durée
28 heures (généralement 4 jours pauses comprises)
Pré requis
Basic understanding of search problems and optimization
Aperçu
Ce cours de quatre jours vise à expliquer le fonctionnement des algorithmes génétiques. il explique également comment sélectionner les paramètres de modèle d'un algorithme génétique; Ce cours a de nombreuses applications pour les algorithmes génétiques et les problèmes d’optimisation sont abordés avec les algorithmes génétiques.
Machine Translated
Plan du cours
Day 1:
- What is a genetic algorithm?
- Chromosome fitness
- Choosing the random initial population
- The crossover operations
- A numeric optimzation example
Day 2
- When to use genetic algorithm
- Coding the gene
- Local maximums and mutation operation
- Population diversity
Day 3
- The meaning and effect of each genetic algorithm parameter
- Varying genetic parameters
- Optimizing scheduling problems
- Cross over and mutation for scheduling problems
Day 4
- Optimizing program or set of rules
- Cross over and mutation operations for optimizing programs
- Creating a parallel model of the genetic algorithm
- Evaluating the genetic algorithm
- Applications of genetic algorithm
Nos Clients témoignent
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Réduction spéciale
12/09/2019 - 09:30
Ghent
01/13/2020 - 09:30
Bruxelles, Centre d'affaires Copernico Science14
01/29/2020 - 09:30
Liège, Place des Guillemins
02/24/2020 - 09:30
Namur, Hotel de Ville
05/19/2020 - 09:30
Bruxelles, Centre d'affaires Copernico Science14
Nos clients
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_ireland.gif "environmental protection agency (epa) ireland")
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