TY  - JOUR
T1  - Image Feature Extraction using Quantum-PSO and Chaotic Map
AU - Aziz Sahy, Seba 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 7
SP  - 2352
EP  - 2359
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.2352.2359
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.2352.2359
KW  - Particle swarm optimization
KW  -quantum particle swarm optimization
KW  -chaotic number generator
KW  -logistic map
KW  -simplification
KW  -efficiency
AB  - One of the population-based heuristic global search algorithms is the Particle Swarm Optimization
(PSO) algorithm that is motivated through patterns of social behavior of organisms which live and interact
within large groups. The PSO is depended on researches on swarms such as fish schooling and bird flocking
Quantum Particle Swarm (Q-PSO) algorithm based on quantum individual, the theory of quantum used the
change the adapting mode of the particles. In this study, Q-PSO algorithm was used in order to enhance the
speed of search and the convergence precision and guarantee the effectiveness and simplification. It is simpler
and more powerful than the algorithms available. The simulation and its application in the feature extraction
prove its high efficiency.
ER  -