利用自适应混沌遗传粒子群算法反演瑞雷面波频散曲线

杨博1,2,3 熊章强1,2,3 张大洲1,2,3 杨振涛4

(1.中南大学有色金属成矿预测与地质环境监测教育部重点实验室, 湖南长沙 410083)
(2.有色资源与地质灾害探查湖南省重点实验室, 湖南长沙 410083)
(3.中南大学地球科学与信息物理学院, 湖南长沙 410083)
(4.南方科技大学地球与空间科学系, 广东深圳 518055)

【摘要】为了提高瑞雷面波频散曲线的反演精度,减少反演过程中的多解性,获取更准确的地下横波速度结构,本文从反演算法入手,对基本的粒子群算法进行改进,提出了一种能同步提高全局和局部搜索能力的自适应混沌遗传粒子群算法(ACGPSO):即先采用自适应惯性权重,并设置粒子的节速度,再引入遗传算法的交叉和变异操作及单维全分量的混沌局部搜索。利用该算法对理论模型的无噪和含噪基阶频散曲线进行反演,且针对含噪数据加入二阶与三阶频散曲线进行联合反演。所得反演结果与常规粒子群算法反演结果的对比表明:ACGPSO算法具有更好的稳定性和抗噪性,且基于该算法的联合反演能有效降低解的多解性,显著提高解的精度。对实际数据所做的两步法反演的效果进一步验证了该算法的适用性。

【关键词】 瑞雷面波; 频散曲线; 粒子群算法; 自适应混沌遗传粒子群算法; 联合反演;

【DOI】

【基金资助】 国家自然科学基金项目“近地表三维复杂介质中瑞雷波传播特性研究”(41274123) 国家重点研发计划“深地资源勘查开采”重点专项“深部资源勘查数据处理、解释软件平台开发及综合示范”(2018YFC0603600) 中南大学中央高校基本科研业务费专项资金资助项目“快速多模式瑞雷面波频散曲线正反演研究”(502211928)

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This Article

ISSN:1000-7210

CN: 13-1095/TE

Vol 54, No. 06, Pages 1217-1227+1172

December 2019

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Article Outline

摘要

  • 0 引言
  • 1 粒子群算法的基本原理及其改进
  • 2 理论模型试算
  • 3 实测数据反演
  • 4 结论
  • 参考文献