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3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm
Liu, Sheng2,3,4; Jin, Shuanggen1,4
刊名PURE AND APPLIED GEOPHYSICS
2020-02-01
卷号177期号:2页码:1005-1027
关键词Fuzzy entropy discrete-valued inversion gravity inversion parameter search fuzzy C-means algorithm
ISSN号0033-4553
DOI10.1007/s00024-019-02306-0
英文摘要The geophysical inversion with combining prior information is very important for resource exploration and studies of the Earth's internal structure. Guided fuzzy C-means clustering inversion (FCM) is normally applied for the Tikhonov regularized inversion, but has the shortcoming of uniform model parameter shrinkage, leading to inaccuracy. In this paper, an improved guided fuzzy clustering algorithm is proposed by adding a fuzzy entropy term to the original guided FCM. This method not only enforces the discrete values to a high degree of approximation by guiding the recovered model to cluster tightly around the known petrophysical property values, but also calculates the distributed characteristics of the model parameter set. Based on this method, the shortcoming of uniform shrinkage of the original guided FCM clustering algorithm is improved, and more accurate inversion results are obtained, making the FCM method more efficient and broadly applicable. Furthermore, a new parameter search algorithm is proposed to accelerate the search speed. The results recovered by using this method with three kinds of theoretical gravity anomaly data show more accurate density anomalies compared with the results generated from the original guided FCM clustering inversion and greater efficiency in the parametric search process when using the new parameter search algorithm. The improved FCM clustering algorithm could enable more extensive and efficient use of gravity inversion.
WOS关键词SMOOTH ; MODELS
WOS研究方向Geochemistry & Geophysics
语种英语
出版者SPRINGER BASEL AG
WOS记录号WOS:000511540200025
内容类型期刊论文
源URL[http://ir.bao.ac.cn/handle/114a11/54558]  
专题中国科学院国家天文台
通讯作者Jin, Shuanggen
作者单位1.Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing 210044, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Xinjiang Astron Observ, Urumqi 830011, Peoples R China
4.Chinese Acad Sci, Shanghai Astron Observ, Shanghai 200030, Peoples R China
推荐引用方式
GB/T 7714
Liu, Sheng,Jin, Shuanggen. 3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm[J]. PURE AND APPLIED GEOPHYSICS,2020,177(2):1005-1027.
APA Liu, Sheng,&Jin, Shuanggen.(2020).3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm.PURE AND APPLIED GEOPHYSICS,177(2),1005-1027.
MLA Liu, Sheng,et al."3-D Gravity Anomaly Inversion Based on Improved Guided Fuzzy C-Means Clustering Algorithm".PURE AND APPLIED GEOPHYSICS 177.2(2020):1005-1027.
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