Abstract
Inversion of Rayleigh wave dispersion curves not only undergoes computational difficulties associated with being trapped by local minima for most local-search methods but also suffers from the high computational time for most global optimization methods due to its multimodality and its high nonlinearity. In order to effectively overcome the above described difficulties, we proposed a new Rayleigh wave inversion scheme based on an ant colony optimization, a commonly used swarm intelligence algorithm. The calculation efficiency and stability of the proposed procedure are tested on a five-layer synthetic model and a real-world example. Results from both synthetic and real field data demonstrate that ant colony optimization applied to nonlinear inversion of Rayleigh waves should be considered good not only in terms of computation time but also in terms of accuracy due to its global and fast convergence in the final stage of exploration.
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Xu, J., Song, X. (2012). Ant Colony Optimization for Nonlinear Inversion of Rayleigh Waves. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_49
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DOI: https://doi.org/10.1007/978-3-642-24553-4_49
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