地震前兆数据的大数据挖掘研究

Research on Big Data Mining of Earthquake Precursor Data

为了能够合理使用地震前兆数据,就要实现地震前兆数据的有效挖掘;目前,在地震千兆观测项及方法不断增加的过程中,传统数据分析方法已经无法满足观测数据分析需求,大数据挖掘技术的出现为地震前兆观测工作带来了较为积极的影响;首先对现代大数据挖掘技术进行全面的分析,之后分析地震预报过程中的大数据挖掘技术,主要流程为分析地震预报方法、寻找地震地区的相关性、获得数据、实现数据预处理,关联规则数据挖掘算法;然后对传统地震前兆数据挖掘技术进行创新为基于时间序列数据流的增量式挖掘,对地震前兆数据挖掘数据进行定义,从时间序列中抽取模式,确认重要点,从而实现数据并行挖掘;最后对设计的大数据挖掘算法进行验证,表示文章所分析的地震前兆数据挖掘算法良好,具有实际使用意义,能够为相关方面提供参考。

In order to make reasonable use of earthquake precursor data,it is necessary to effectively mine earthquake precursor data.At present,in the process of increasing seismic gigabit observation items and methods,traditional data analysis methods can no longer meet the needs of observation data analysis.The emergence of big data mining technology has brought apositive impact on earthquake precursor observation work.Firstly,the modern big data mining technology is comprehensively analyzed,and then the big data mining technology in the earthquake prediction process is analyzed.The main processes are analyzing the earthquake prediction method,finding the correlation of the earthquake area,obtaining the data,realizing the data preprocessing,and correlating the rule data.Mining algorithm.Then the traditional earthquake precursor data mining technology is innovated into incremental mining based on time series data stream,which defines the data of earthquake precursor data mining,extracts patterns from time series,confirms important points,and realizes data parallel mining.Finally,the design of the big data mining algorithm is verified,which indicates that the seismic precursor data mining algorithm analyzed in this paper is good,has practical use significance,and can provide reference for relevant aspects.