DocumentCode :
2855953
Title :
A High-Accuracy Parameter Estimation PSO Algorithm
Author :
Yin, Yan-chao ; Sun, Lin-fu ; Han, Min
Author_Institution :
Center of CAD Eng., Southwest Jiaotong Univ., Chengdu
fYear :
2008
fDate :
29-31 July 2008
Firstpage :
7
Lastpage :
12
Abstract :
A preferable value for parameters proved to be crucial in enhancing the performance and efficiency of particle swarm optimization (PSO) algorithm. To provide good solution for reasonable choice of parameter values within fairly wide range for particle swarm optimization, this paper presents a novel parameter optimizing configuration strategy based on multi-order rhombus thought (MRT), which depends on the optimization function to adaptively configure the most suitable set of parameters. With the divergent-concentrate-redivigent-reconcentrate nature of MRT, parameters are gradually optimized by the rhombus thought process as feedback information of the evolutionary process. Compared with other main improved methods, the computation procedures of MRTPSO algorithm are discussed, and numerical experiments based on typical benchmarks are given to illustrate the better convergence characteristic and shorter executing time of MRTPSO algorithm.
Keywords :
parameter estimation; particle swarm optimisation; MRTPSO algorithm; PSO algorithm; divergent-concentrate-redivigent-reconcentrate nature; evolutionary process; high-accuracy parameter estimation; multi-order rhombus thought; parameter optimizing configuration strategy; particle swarm optimization; Chaos; Conferences; Convergence of numerical methods; Embedded software; Equations; Iterative algorithms; Optimization methods; Parameter estimation; Particle swarm optimization; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Embedded Software and Systems Symposia, 2008. ICESS Symposia '08. International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-0-7695-3288-2
Type :
conf
DOI :
10.1109/ICESS.Symposia.2008.8
Filename :
4627122
Link To Document :
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