• Aucun résultat trouvé

Fouille de données basée algorithmes bio-inspirés

N/A
N/A
Protected

Academic year: 2021

Partager "Fouille de données basée algorithmes bio-inspirés"

Copied!
114
0
0

Texte intégral

Loading

Figure

Figure 2.1: Feature selection process [Dash 1997].
Figure 3.1: The global architecture of the QDEPSO algorithm.
Table 3.1: Lookup table of the rotation angle (x: binary individual, b: best local solution, bg: best global solution, f (.): fitness function )
Table 3.2: The parameters of algorithm.
+7

Références

Documents relatifs

This paper describes the design and development of particle swarm optimization (PSO) based maximum power point tracking (MPPT) algorithm for photovoltaic energy conversion system.

However we limit the scales for the social and individual cognitive factors to dif- ferent values since it has shown a statistically significant improvement in mono-objective PSO

About the convergence of PSO, Van Den Bergh and Engelbrecht (2006) looked at the trajectories of the particles and proved that each particle converges to a stable point

A Novel Distributed Particle Swarm Optimization Algorithm for the Optimal Power Flow ProblemN. Nicolo Gionfra, Guillaume Sandou, Houria Siguerdidjane, Philippe Loevenbruck,

In this paper, one behavior of particle swarms from the domain of physics is integrated into PSO and a compound particle swarm optimization (CPSO) is proposed to address

As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic

As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic

La méthode la plus typique du data mining est certainement celle des arbres de décision : pour prédire une réponse Y, qu’elle soit numérique ou qualitative, on