Journal
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Volume 32, Issue 11, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S021800141859019X
Keywords
Chaos operator; hybrid algorithm; parameter inversion; particle swarm optimization; global optimization
Categories
Funding
- National Natural Science Foundation of China [61662090]
- Science and Technology project of Guizhou [[2017]1207]
- training program of high level innovative talents of Guizhou [[2017]3]
- Guizhou province Natural Science Foundation in China [KY[2016]018]
- Natural Science Foundation of Hunan Province, China [2015JJ410]
- Research Foundation of Education Bureau of Hunan Province, China [13C333, 15C0960]
- Doctoral Fund of Zunyi Normal College [BS[2015]13]
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A chaos particle swarm optimization (CPSO) algorithm based on the chaos operator (CS) is proposed for global optimization problems and parameter inversion of the nonlinear sun shadow model in our study. The CPSO algorithm combines the local search ability of CS and the global search ability of PSO algorithm. The CPSO algorithm can not only solve the global optimization problems effectively, but also address the parameter inversion problems of the date of sun shadow model location successfully. The results of numerical experiment and simulation experiment show that the CPSO algorithm has higher accuracy and faster convergence than the-state-of-the-art techniques. It can effectively improve the computing accuracy and computing efficiency of the global optimization problems, and also provide a novel method to solve the problems of integer parameter inversion in real life.
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