共轭梯度法
粒子群优化
算法
反演(地质)
计算机科学
遗传算法
数学优化
加权
数学
物理
古生物学
构造盆地
声学
生物
作者
Minjie Shi,Wenxuan Shi,Yizhao Gao,Xiaoyu Liu,Biao Yuan
标识
DOI:10.1109/igarss39084.2020.9324110
摘要
The time domain full waveform inversion (FWI) algorithm of ground penetrating radar (GPR) has high accuracy, but it needs a large amount of calculations, and it is easy to fall into the local optimal solution. In this paper, based on the full waveform inversion algorithm and genetic particle swarm optimization (GA_PSO) algorithm, the author proposes a full waveform inversion algorithm called genetic random linear weight particle swarm optimization algorithm guided by conjugate gradient in FWI. This algorithm avoids the calculation of the Hession matrix, and can greatly improve the efficiency of searching the global optimal solution. It can invert two parameters quickly. The paper first introduces particle swarm algorithm (PSO), genetic algorithm (GA) and full waveform inversion algorithm. In the next section, the paper introduces the first innovation point of this research-random linear weight particle swarm optimization based on genetic algorithm (GA_RLPSO). The algorithm changes its inertial weight according to genetic particle swarm algorithm, which brings it have a faster convergence rate. Then the paper introduces the second innovation point-GA_RLPSO with the guidance of conjugate gradient. In this paper, the gradient in-formatiom of full waveform inversion is added to the velocity weighting factor, which can greatly improve the speed and accuracy of the algorithm. Finally, the paper compares the inversion results of several different algorithms, which can prove that the proposed algorithm has the higher accuracy about model reconstruction.
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