scholarly journals An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication

2010 ◽  
Vol 3 (Supplement 1) ◽  
pp. 18 ◽  
Author(s):  
Wenbin Wang ◽  
Qibo Sun ◽  
Xinchao Zhao ◽  
Fangchun Yang
Keyword(s):  
Particle Swarm Optimization ◽  
Web Service ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Service Selection ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Web Service Selection ◽  
Service Oriented

Compressed Sensing Image Reconstruction Based on Improved Particle Swarm Optimization Algorithm

2014 ◽  
Vol 599-601 ◽  
pp. 1453-1456
Author(s):  
Ju Wang ◽  
Yin Liu ◽  
Wei Juan Zhang ◽  
Kun Li
Keyword(s):  
Particle Swarm Optimization ◽  
Image Reconstruction ◽  
Compressed Sensing ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Matching Pursuit ◽  
Particle Swarm ◽  
Premature Convergence ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization

The reconstruction algorithm has a hot research in compressed sensing. Matching pursuit algorithm has a huge computational task, when particle swarm optimization has been put forth to find the best atom, but it due to the easy convergence to local minima, so the paper proposed a algorithm ,which based on improved particle swarm optimization. The algorithm referred above combines K-mean and particle swarm optimization algorithm. The algorithm not only effectively prevents the premature convergence, but also improves the K-mean’s local. These findings indicated that the algorithm overcomes premature convergence of particle swarm optimization, and improves the quality of image reconstruction.

Sign in / Sign up

Export Citation Format

Share Document