DocumentCode :
3461721
Title :
Chaos Particle Swarm Optimization Algorithm for Estimating Solute Transport Parameters of Streams from Tracer Experiment Data
Author :
Guo, Jian-Qing ; Zhou, Hong-Fei ; Meng, Ling-Qun
Author_Institution :
Xinjiang Inst. of Ecology & Geogr., Acad. Sinica, Urumqi, China
fYear :
2009
fDate :
7-9 Dec. 2009
Firstpage :
872
Lastpage :
875
Abstract :
In this paper, we combined chaotic search into standard particle swarm search into one and proposed a new algorithm named as chaos particle swarm optimization algorithm(CPSO). The CPSO algorithm may speed the search process, and improve the ability of seeking the global optimal solution and convergence. And the CPSO algorithm was applied to analysis of one-dimensional tracing test date of river stream with tracer injected instantaneously, and further to optimization of function for estimating the water quality parameters of river stream. The results show that the proposed algorithm is superior to the standard particle swarm optimization one in the speed of search and convergence.
Keywords :
chaos; geophysics computing; hydrological techniques; particle swarm optimisation; rivers; water quality; CPSO algorithm; chaos particle swarm optimization algorithm; chaotic search; global optimal solution; one-dimensional tracing test date; river stream; solute transport parameters; standard particle swarm optimization; tracer experiment data; water quality parameters; Chaos; Environmental factors; Geography; Geology; Optimization methods; Parameter estimation; Particle swarm optimization; Rivers; Stochastic processes; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
Type :
conf
DOI :
10.1109/ICICIC.2009.136
Filename :
5412634
Link To Document :
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