改进主成分分析方法及其在地震数据处理中的应用  

Improved Primary Component Analysis Method and Its Application in Seismic Data Analysis

作　　者：田书英[1] 李玥姮[2] 辛小龙[1] 贺瑞缠[1] 陈振勋 

机构地区：[1]西北大学,西安710127 [2]西安交通大学电子与信息工程学院,西安710049

出　　处：《价值工程》2011年第29期3-4,共2页Value Engineering

基　　金：国家大学生创新性实验计划项目(国081069714)

摘　　要：本文基于地震数据的特征,引入向量成分化概念,提出了一种改进的PCA方法,并给出了相应的算法实现。应用改进后的PCA方法,分析了西安高陵2009年11月5日地震的前兆数据以及之前发生在西安地区的多次地震的前兆数据。分析结果表明:这种改进的PCA方法在处理地震数据时,主成分数据拟合曲线的震前特征更便于数学表示,为地震的分析和预测提供了良好的基础。This paper introduces the concept of vecter of proportions based on the characteristics of seismic data and presents an improved method of principal component analysis and a way to carry out it. Then we apply the improved PCA method to the precursor data of Gaoling earthquake which happened in Xi＇an in November 5, 2009, as well as other precursor datas of earthquakes which happened in Xi＇an before. The results show that this improved PCA method makes the pre-earthquake characteristics lie in the principal component data fitting curve more easier to express in mathematic when processing seismic data and that provides a good basis for earthquake analysis and prediction.

关 键 词：地震数据 成分向量 主成分分析(PCA) 贡献率 

分 类 号：P315[天文地球—地震学]