必须声明标量变量 "@Script_ID"。 基于K中心点聚类分析的大地电磁阻抗识别-《地球科学与环境学报》
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[1]赵玄,严家斌,皇祥宇,等.基于K中心点聚类分析的大地电磁阻抗识别[J].地球科学与环境学报,2018,40(06):779-786.
 ZHAO Xuan,YAN Jia-bin,HUANG Xiang-yu,et al.Magnetotelluric Impedance Recognition Based on K-medoids Clustering Analysis[J].Journal of Earth Sciences and Environment,2018,40(06):779-786.
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基于K中心点聚类分析的大地电磁阻抗识别(PDF)
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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:
第40卷
期数:
2018年第06期
页码:
779-786
栏目:
应用地球物理
出版日期:
2018-11-15

文章信息/Info

Title:
Magnetotelluric Impedance Recognition Based on K-medoids Clustering Analysis
文章编号:
1672-6561(2018)06-0779-08
作者:
赵玄严家斌皇祥宇胡涛
1.中南大学地球科学与信息物理学院,湖南 长沙 410083; 2.中南大学有色资源与地质灾害探查湖南省重点实验室,湖南 长沙 410083
Author(s):
ZHAO Xuan YAN Jia-bin HUANG Xiang-yu HU Tao
1. School of Geosciences and Info-physics, Central South University, Changsha 410083, Hunan, China; 2. Key Laboratory of Non-ferrous Resources and Geological Hazard Detection of Hunan Province, Central South University, Changsha 410083, Hunan, China
关键词:
阻抗估计实虚分量聚类分析K中心点阻抗欧氏距离相干度紧凑性数值模拟
Keywords:
impedance estimation real and imaginary components clustering analysis K-medoids euclidean distance for impedance coherence compactedness numerical simulation
分类号:
P631.3+25
DOI:
-
文献标志码:
A
摘要:
在大地电磁场复杂的观测环境中,信号会受到不同类型或程度的噪声干扰。传统阻抗估计或提取方法(如功率谱法、Robust法等)难以获得稳定的阻抗值。利用大地电磁阻抗的实虚分量特性,受噪声干扰小的信号阻抗分布集中,受噪声干扰严重的信号阻抗分布散乱。引入K中心点聚类分析对阻抗进行提取与识别,并利用阻抗欧氏距离来描述阻抗间的相似性,依据相似性把受干扰小的信号阻抗划分到一类,受干扰大的信号阻抗划分到不同的类。依据相干度准则和紧凑性准则等类的选取准则,甄别出干扰环境中阻抗所在的最佳类。通过仿真实验和实例分析,验证了K中心点聚类分析能在噪声环境中识别出高质量的信号,恢复出真实阻抗值。
Abstract:
In the complicated observation environment, the magnetotelluric signal is disturbed by different types or degrees of noise. Traditional estimation and extraction methods are hard to obtain stable impedance, such as the power-spectrum method and Robust method. Based on the physical properties of the real and imaginary components of magnetotelluric impedance, the impedance of signal disturbed slightly by noise distributes intensively, and the impedance of signal disturbed severely by noise distributes dispersedly. So, the impedance extraction and identification based on K-medoids clustering analysis was introduced, and then the euclidean distance for impedance was proposed to describe the similarity of impedance. The K-medoids clustering analysis can divide the impedance of signal disturbed slightly by noise into the same cluster and other impedance of signal disturbed severely by noise into different clusters based on the similarity. According to the selection criteria of cluster including coherence and compactedness criteria, the optimal cluster of impedance in the disturbed environment was chosen. Based on the simulation experiment and instance analysis, the K-medoids clustering analysis can recognize high quality signal in noisy environment and recovery the real impedance.

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备注/Memo

备注/Memo:
收稿日期:2018-03-16;修回日期:2018-07-11
基金项目:国家自然科学基金项目(40874055);湖南省自然科学基金项目(14JJ2012)
作者简介:赵 玄(1992-),男,安徽阜阳人,工学硕士研究生,E-mail:2625476614@qq.com。
通讯作者:严家斌(1969-),男,湖南常德人,教授,工学博士,E-mail:cspyry@csu.edu.cn。
更新日期/Last Update: 2018-12-06