Title :
Hybrid particle swarm optimization algorithm and its application
Author :
Zhengwei Li ; Guojun Tan ; Hao Li
Author_Institution :
Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
Abstract :
Inverse problem plays an important role in seismic exploration. Much effort has been devoted over the past several decades to develop and improve the seismic inverse methods. Traditional linear inversion methods like Newton method and Newton-like methods may not be optimal convergent if a good initial estimate cannot be provided. In this paper, an effective immune-based particle swarm optimization (IPSO) is proposed for solving seismic inverse problem. The proposed IPSO improves the ability to find the globally excellent result and the convergence speed which introduces update and mutation operators and the population recombination mechanism. Numerical simulation and comparisons with other methods demonstrate the effectiveness and robustness of the proposed algorithm. The practical results show that the proposed algorithm is fit for seismic inverse problem.
Keywords :
Newton method; earthquakes; geophysics; particle swarm optimisation; Newton method; hybrid particle swarm optimization; immune-based particle swarm optimization; mutation operators; population recombination mechanism; seismic exploration; seismic inverse methods; update operators; Algorithm design and analysis; Biological cells; Equations; Immune system; Mathematical model; Optimization; Particle swarm optimization; hybrid algorithm; immune operators; inverse problem;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584841