Inversion of Rayleigh surface wave dispersion curve by hybrid particle swarm optimization algorithm
CHEN Hao1, LI Hongxing1, LI Tao1,2, AI Hanbing1, ZHANG Jiahui1, DAI Tianyu3
1. State Key Laboratory of Nuclear Resources and Environment, East China University of Technology, Nanchang, Jiangxi 330013, China; 2. Guangzhou Construction Engineering Quality Safety Checking & Measuring Center, Guangzhou, Guangdong 510440, China; 3. School of Mathematics and Computer Sciences, Nanchang University, Nanchang, Jiangxi 330031, China
Abstract:The surface wave dispersion curve inverted by traditional particle swarm algorithms is easy to fall into the local extremum. In view of this problem, this paper optimizes the inversion through three strategies including nonlinear adaptive inertia weights, compression factors, and boundary condition constraints and proposes a hybrid particle swarm optimization (HPSO) to invert the Rayleigh surface wave dispersion curve, which improves the accuracy of the inversion and reduces the multi-solution of the inversion. Through the inversion of noiseless, noisy, and multimodal theoretical dispersion curves of typical geological models, the effectiveness, anti-noise ability, and joint inversion ability of multimodal dispersion curves of the method are verified. The inversion results show that compared with boundary-constrained particle swarm optimization, HPSO has higher inversion accuracy. Finally, the inversion of data measured in a certain area of Iceland verifies the applicability of HPSO.
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