多维有序聚类法在地质数据分类中的应用  

Application of multi-dimension sequential clustering method in geological data classification

作　　者：余翔[1] 白友良[1] 李成[1] 赵楠[1] 

机构地区：[1]西北核技术研究所,西安710024

出　　处：《计算机应用》2015年第A01期152-155,共4页journal of Computer Applications

摘　　要：针对经验法在地质多指标数据进行有序分类存在局限性的问题,提出了基于Fisher最优分割的多维有序聚类法,通过对均一化处理的多维指标之间定义类直径的损失函数来判别最优分割,然后在使得损失函数最小的情况下合并相邻分类,实现有序样本数据的聚类层次。采用该方法对钻孔编录地层划分、岩体质量分级和孢粉粒度分带三种数据进行分类,结果表明在不能确定分层数的情况下,可以利用损失函数的导数曲线极值点确定最优分层数;样品多个指标之间的相关性越高,分类结果与单指标分类结果的差异越不明显。该方法能够为多元地质数据的定量分析提供数学理论依据,也可以应用于其他行业领域。In order to solve the limitation problem of empirical approach in classification of sequential multi-index geological data, multi-dimensional sequential clustering method based on Fisher optimal segmentation was proposed to achieve hierarchical clustering. The multi-index of sample data was homogenized first, and then the category diameter of each possible segments was calculated to find optimal segmentation. The optimal segmentation had a minimum value of loss function. At last adjacent categories with smallest diameter were merged in proper order to keep orderliness. Through the applications of stratigraphic sequence division, rock mass classification and spore-pollen graininess zonation, the result shows that the number of segments can be specified by extreme points of derivative curve of loss function, and the classifications are consistent with other studies. The higher the correlation between multiple indexes is, the more similar the results of classification are with the results of single index. The method provides the mathematic theory basis in quantitative analysis of geologic data processing and it also can be used in other fields.

关 键 词：多维有序聚类法 数据分类 地层划分 岩体质量分级 孢粉粒度分带 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]