Swarm intelligence optimization and its application in geophysical data inversion

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Abstract The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems: (1) a linear problem which is sensitive to noise, (2) a synchronous inversion of linear and nonlinear problems, and (3) a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.

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	YUAN San-Yi
	WANG Shang-Xu
	TIAN Nan

Key words： Swarm intelligence optimization geophysical inversion multimodal particle swarm optimization algorithm

Received: 2008-11-15;

Fund:

This research was financially supported by the 973 Program (Grant No 2007CB209600) and Open Fund (No. GDL0706) of the Key Laboratory of Geo-detection (China University of Geosciences, Beijing), Ministry of Education.

Cite this article:

YUAN San-Yi,WANG Shang-Xu,TIAN Nan. Swarm intelligence optimization and its application in geophysical data inversion[J]. APPLIED GEOPHYSICS, 2009, 6(2): 166-174.

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