文献类型：期刊文献

英文题名：Application of data mining technology in real-Time large capacity data analysis

作者：Zhang, Qin[1]; Liu, Yutang[2]

第一作者：张秦

机构：[1] School of Mathematics and Information Science, Xinxiang University, Xinxiang, 453003, China; [2] Department of Basic Subjects, Henan Institute of Technology, Xinxiang, 453002, China

第一机构：新乡学院数学与信息科学学院

年份：2017

卷号：32

期号：11

起止页码：1-6

外文期刊名：Revista de la Facultad de Ingenieria

收录：EI(收录号：20174904498436)

语种：英文

外文关键词：Cluster analysis - Data acquisition - Data handling - Information analysis - Leak detection - Leakage (fluid) - Petroleum transportation - Pipelines

摘要：With the development of data mining technology, the method of data mining has been widely used in all walks of life. The advent of data mining methods has enabled people to eventually understand the true value of data. In the field of industrial control, the analysis and processing of real-Time data can be seen everywhere, and the use of data mining method for data preprocessing, timing data analysis and abnormal data analysis and processing is a relatively new topic. This work introduces the theory and method of data mining, including the definition of data mining, the main process of mining, classification and the main technical means. At the same time, the clustering analysis and abnormal data mining methods in data mining are mainly studied, taking the pressure data acquisition and analysis of oil and gas gathering and transportation pipeline as an example, the methods of cluster analysis and abnormal data mining are studied. Aiming at the actual situation of the leak detection project of the oil-gas gathering and transportation pipeline, the process of data pretreatment is put forward, and then use the method of abnormal data mining to carry out real-Time and large-capacity data analysis.