基于数据密度确定分布区域的方法：以TAS图解分析为例  

Determination of distribution region based on data density： A case study of TAS diagram

作　　者：葛粲[1,2,3] 顾海欧 汪方跃[1,2,3] 李修钰[4] 周宇章[5] 袁峰[1,2,3] Ge Can;Gu Haiou;Wang Fangyue;Li Xiuyu;Zhou Yuzhang;Yuan Feng(School of Resources and Environmental Engineer,Hefei University of Technology,Hefei 230009;Laboratory of Three-Dimension Exploration for Mineral District,Hefei University of Technology,Hefei 230009;Anhui Province Engineering Research Center for Mineral Resources and Mine Environments,Hefei University of Technology,Hefei 230009;Geological Survey of Anhui Province,Hefei 230001;Public Geological Survey Management Center of Anhui Province,Hefei 230001)

机构地区：[1]合肥工业大学资源与环境工程学院,合肥230009 [2]合肥工业大学矿集区立体探测实验室,合肥230009 [3]合肥工业大学安徽省矿产资源与矿山环境工程技术研究中心,合肥230009 [4]安徽省地质调查院,合肥230001 [5]安徽省公益性地质调查管理中心,合肥230001

出　　处：《地质科学》2018年第4期1240-1253,共14页Chinese Journal of Geology(Scientia Geologica Sinica)

基　　金：国家青年科学基金项目（编号：41504042）、国家重点研发计划项目（编号：2016YFC0600209）、国家自然科学基金项目（编号：41702353,41672069）和安徽省国土资源科技项目（编号：2016-K-4）资助.

摘　　要：为了客观地确定数据点投图后分布的主要区域，本文提出了一种基于数据密度确定数据主要分布区域的方法。利用该方法可以更加直观地了解数据分布，并可以作为数据清洗的预处理手段。本文基于GEOROC大数据．以全碱对硅（TAS）图解为例，进行了分析和验证。通过提取GEOROC数据库中与TAS图解相关的岩石样本中SiO2、Na2O、K2O和烧失量含量数据，通过数据常规清洗和归算，最终获得24个种类合计13．3万条有效数据。通过数据投点、分区统计和提取80％数据的分布区域，验证了24种岩石样品与TAS图解的吻合程度。通过综合研究分析发现，有6类岩石的数据分布与TAS图解定义区域基本一致，18类岩石的数据分布与TAS图解定义区域有系统性偏差。大数据研究证明了TAS图解的不足之处，利用全碱和SiO2作为指标，难以实现提升总体分类的准确性。In order to determine the main distribution areas of data points after mapping, this paper proposes an automatic distribution area determination method based on data density. The method can be used to understand the data distribution more intuitively and can be used as a preprocessing means for data cleaning. Based on GEOROC database, the total alkali vs. silicon （TAS） diagram is analyzed and verified in this paper. By extracting SiO2, Na20, K20 and LOI of rock samples related to TAS diagram in GEOROC database, about 133 thousand valid data of 24 rock types were obtained through routine data cleaning and reduction. The agreement between 24 rock samples and TAS diagram was verified by data points mapping, partition statistics and 80% data distribution area extraction. Through comprehensive research and analysis, it is found that the data distribution of 9 rock types is basically consistent with TAS diagram definition area, and the data distribution of 15 rock types has systematic deviation in TAS diagram definition area. Big data research has proved the deficiency of the TAS diagram. Using Total-Alkali and SiO2 as indicators, it is difficult to improve the accuracy of the overall classification.

关 键 词：大数据 数据分布区域提取 密度分布 TAS图解 

分 类 号：P588.1[天文地球—岩石学]