Title :
An optimized quantum particle swarm algorithm based on the D-dimensional hyper-chaotic discrete system equation
Author :
Yangjun, Li ; Xia, Jin Yan ; Gao, Wang
Author_Institution :
Key Lab. of Instrum. Sci. & Dynamic Meas., North Univ. of China, Taiyuan, China
Abstract :
Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm inspired by social behavior patterns of organisms that research on such as fish schooling and bird flocking. This essay presents a new Quantum-behaved PSO (QPSO) algorithm using hyper-chaotic discrete system equation, as h-QPSO. The simulation results of the classical function have demonstrated that the h-QPSO algorithm is superior to the classical PSO algorithm and the quantum PSO algorithm in its performance.
Keywords :
discrete systems; particle swarm optimisation; D-dimensional hyper-chaotic discrete system equation; optimized quantum particle swarm algorithm; particle swarm optimization; population-based swarm intelligence algorithm; social behavior patterns; Algorithm design and analysis; Convergence; Equations; Mathematical model; Optimization; Particle swarm optimization; Presses; hyper-chaotic sequence; identical particle system; particle swarm optimization; search algorithm; seasonal fluctuation;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5622858