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针对目前线性化和非线性化算法在面波频散曲线反演中的局限性问题,分析了一种新的非线性全局优化算法——粒子群算法(PSO)及其基本原理和算法流程,并且采用了细化分层理论与粒子群算法相结合的方法,在求解横波速度结构的基础上,分别对四层速度递增理论模型和野外实测数据进行了反演试算.实验结果表明:频散曲线反演拟合效果较好,粒子群算法表现出了全局寻优特点.研究结论初步验证了粒子群算法在面波频散曲线反演中的可行性与有效性.
Aiming at the limitation of current linearization and non-linearization algorithms in surface wave dispersion curve inversion, a new non-linear global optimization algorithm-Particle Swarm Optimization (PSO), its basic principle and algorithm flow are analyzed. Based on the solution of the shear-wave velocity structure, the theoretical model of the four-layer velocity increment and the measured data in the field were respectively inversed and calculated.The experimental results show that the frequency The fitting result of scattered curve is better, and the PSO algorithm shows the characteristics of global optimization.The research conclusion proves the feasibility and effectiveness of particle swarm algorithm in the inversion of surface wave dispersion curve.