基于费雪分布的模糊 K-Means 算法,用于识别岩石不连续集

IF 7 1区 工程技术 Q1 ENGINEERING, GEOLOGICAL
André Monteiro Klen , Stefano Bonduà , Sara Kasmaeeyazdi , Milene Sabino Lana , Danielle Aparecida de Menezes , Pedro Gabriel de Carvalho
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引用次数: 0

摘要

岩石的不连续性对岩体的机械和水力行为有重大影响。岩石工程的一个重要方面是将方向相似的不连续面归类。为此,人们采用了 K-Means 和模糊 K-Means (FKM) 等聚类算法。然而,这些算法的结果受到初始聚类中心选择的影响。本文提出了一种基于费舍尔分布(FFKM)的改进型 FKM 算法,用于自动识别岩石不连续集。该算法利用费舍尔分布生成并选择合适的初始聚类中心。FFKM 的性能最初通过一个已公布的数据集进行了验证,并将其结果与其他常用于不连续面分组的聚类方法进行了比较。结果表明,FFKM 的性能优于 FKM 算法,可与其他方法相媲美。随后,所提出的算法被用于分析在露天铁矿采样的断裂数据集。FFKM 算法有助于识别正确的集合数量,其结果与现场观察到的断裂集合一致。最后,使用人工不连续数据集对该算法进行了验证,结果表明该方法正确识别了数据集的数量,并提供了与原始数据集类似的不连续数据集。FFKM 算法具有显著的优势:它保持了 FKM 算法的基本特征,有效地解决了选择合适的初始群集中心的难题,只需要将预期的不连续集数量作为输入参数,在可接受的计算时间内处理数据,可作为定义不连续集数量的工具,并减轻了立体投影法的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fuzzy K-Means algorithm based on Fisher distribution for the identification of rock discontinuity sets

Rock discontinuities significantly impact the mechanical and hydraulic behavior of rock masses. A crucial aspect of rock engineering involves classifying discontinuities with similar orientations into groups. For this purpose, clustering algorithms, such as K-Means and Fuzzy K-Means (FKM), have been employed. However, the outcomes of these algorithms are influenced by the selection of initial cluster centers. This paper proposes an improved FKM algorithm to automatically identify rock discontinuity sets based on the Fisher distribution (FFKM). The algorithm uses the Fisher distribution to generate and select appropriate initial cluster centers. The performance of FFKM was initially validated using a published data set, and its results were compared with other clustering methods commonly used for grouping discontinuities. Results demonstrated the superior performance of FFKM over the FKM algorithm, comparable to other methods. Subsequently, the proposed algorithm was employed to analyze a fracture data set sampled at an open-pit iron mine. The FFKM facilitated identifying the correct number of sets and produced results consistent with the fracture sets observed in the field. Finally, the algorithm was verified using an artificial discontinuity data set, and the results demonstrated that the method correctly identified the number of sets and provided discontinuity sets similar to the original data set. The FFKM algorithm offers significant advantages: it maintains the essential characteristics of the FKM algorithm, effectively addresses the challenge of selecting suitable initial cluster centers, requires only the expected number of discontinuity sets as an input parameter, processes data within an acceptable computation time, serves as a tool for defining the number of discontinuity sets, and mitigates the drawbacks of the stereographic projection method.

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来源期刊
CiteScore
14.00
自引率
5.60%
发文量
196
审稿时长
18 weeks
期刊介绍: The International Journal of Rock Mechanics and Mining Sciences focuses on original research, new developments, site measurements, and case studies within the fields of rock mechanics and rock engineering. Serving as an international platform, it showcases high-quality papers addressing rock mechanics and the application of its principles and techniques in mining and civil engineering projects situated on or within rock masses. These projects encompass a wide range, including slopes, open-pit mines, quarries, shafts, tunnels, caverns, underground mines, metro systems, dams, hydro-electric stations, geothermal energy, petroleum engineering, and radioactive waste disposal. The journal welcomes submissions on various topics, with particular interest in theoretical advancements, analytical and numerical methods, rock testing, site investigation, and case studies.
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