Effective categorization of joints by k-means and cluster analysis its verification by Fisher distribution

SUN Xian-chun; WAN Li; JIANG Xiao-wei

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Effective categorization of joints by k-means and cluster analysis its verification by Fisher distribution

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- Effective categorization of joints by k-means and cluster analysis its verification by Fisher distribution
- Vol. 29, Issue S1, (2008)
- 作者机构：
  
  中国地质大学(北京) 水资源与环境学院,北京,100083
- 作者简介：
- 基金信息：
- DOI：
  CLC： P583
- Online First：15 April 2016，
  
  Published：2008
- 稿件说明：
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SUN Xian-chun, WAN Li, JIANG Xiao-wei. Effective categorization of joints by k-means and cluster analysis its verification by Fisher distribution[J]. 2008, 29(S1).
DOI：

SUN Xian-chun, WAN Li, JIANG Xiao-wei. Effective categorization of joints by k-means and cluster analysis its verification by Fisher distribution[J]. 2008, 29(S1). DOI：

摘要

裂隙岩体内的节理往往是变化的，有时甚至变化很大。测得大量节理产状以后，对其分组是一项基础性的工作，但是如何分组目前还没有很好的理论和方法。采用快速聚类分析的方法，将节理产状的样本数据划分为不同的簇，利用极大似然估计的原理，通过数值方法求解费歇尔概率分布模型的参数，并用皮尔逊检验说明了费歇尔逊概率模型的有效性。通过不同簇的概率模型计算及其簇心的分布特性比较说明了簇数分类的适度性。利用所提出的快速聚类分析方法及其推导的计算公式，可以方便地求解费歇尔分布的参数。结合皮尔逊检验，形成了解决这类问题的系统实用的方法。

Abstract

The joints that constitute the fractured rock masses normally change dramatically. After measuring the orientation of numerous joints in a given area

it is imperative to categorize the joints. Unfortunately

there is no widely accepted method to categorize joints at present. Joints are categorized into several clusters by using quick cluster analysis. The parameters of Fisher distribution model are estimated by maximum likelihood

and the model is finally verified by using Pearson test. The results demonstrate that the categorized clusters must be suitable

otherwise cluster centroids would change dramatically and the data around the centroids are not continuous

which leads to the failure of Pearson test. By using the proposed methods

it is effective to categorize the fissures in practice.

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