Fuzzy Edge Detection In Computed TomographyThrough Particle Swarm Optimization

To overcome the above problems when using the multi- population method, CPSO employs a global search method to detect promising sub-regions and a hierarchical clustering method

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

We propose a new combined approach using particle swarm optimization (PSO) and fuzzy inference penalty, which will be helpful to elevate the hard inverse problem of 3 D

We propose a new combined approach using particle swarm optimization (PSO) and fuzzy inference penalty, which will be helpful to elevate the hard inverse problem of 3D

This was a handicap facing the challenge of determining the 3D exact defect form.This paper presents a method for 3D image reconstruction, the most interesting in non

Particle Swarm Optimization Of Fuzzy Penalty For 3D Image Reconstruction In X-Ray Tomography.. A.M.T.Gouicem 1 , M.Yahi 1 , A.Taleb-Ahmed 2 ,

If we take J(f) as a fitness function to optimize by the PSO we will express the Value of the prior term in MAP criteria with fuzzy model in our method FP PSO (fuzzy penalty

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