基于滑动窗口的几何移动平均鞅算法在震前异常分析中的应用

计算机应用 ›› 2013, Vol. 33 ›› Issue (12): 3608-3610.

• 典型应用 • 上一篇

基于滑动窗口的几何移动平均鞅算法在震前异常分析中的应用

陈丽萍¹,孔祥增²,郑之¹,林新棋¹,詹晓珊¹

1. 福建师范大学数学与计算机科学学院，福州 350007；
2. 阿尔斯特大学计算与数学学院, 英国北爱尔兰 BT37 0QB

收稿日期:2013-04-22 修回日期:2013-06-20 出版日期:2013-12-01 发布日期:2013-12-31
通讯作者: 陈丽萍
作者简介:陈丽萍(1977-),女,福建宁德人,副教授,硕士,主要研究方向:人工智能、数据挖掘;
孔祥增(1981-),男,福建龙岩人,实验师,博士研究生,主要研究方向:数据挖掘、人工智能、数字水印;
郑之(1983-),男,福建福州人,讲师,博士研究生,主要研究方向:数据挖掘;
林新棋(1972-),男,福建莆田人,副教授,博士,主要研究方向:多媒体信息处理、数据挖掘;
詹晓珊(1988-),女,福建福州人,硕士研究生,主要研究方向:多媒体信息处理、数据挖掘。
基金资助:
国家自然科学基金资助项目;英国阿尔斯特大学VCRS奖学金资助项目

Application of geometric moving average martingale algorithm in anomaly analysis before earthquake based on sliding window

CHEN Liping¹,KONG Xiangzeng²,ZHEN Zhi¹,LIN Xinqi¹,ZHAN Xiaoshan¹

1. College of Mathematics and Computer Science, Fujian Normal University, Fuzhou Fujian 350007,China;
2. School of Computing and Mathematics, University of Ulster, Northern Ireland UK BT37 0QB, UK

Received:2013-04-22 Revised:2013-06-20 Online:2013-12-31 Published:2013-12-01
Contact: CHEN Liping

摘要/Abstract

摘要： 在地震发生前往往存在各种异常现象，而如何有效地提取震前异常信息是非常重要的研究课题。采用一种基于滑动窗口的几何移动平均鞅算法来进行震前异常特征提取。该算法将地震数据进行几何移动平均鞅处理和滑动窗口特征抽取后，能够有效地提取地震震前异常数据的特征。利用该算法对汶川地震和庐山地震震前的美国国家海洋和大气管理局(NOAA)卫星长波辐射信息进行了分析。实验结果表明该算法能够发现震中区域比周边区域存在更明显的异常,这些异常信号可以辅助研究人员在震前确定地震区域。

关键词: 滑动窗口, 几何移动平均鞅, 地震, 异常分析, 特征抽取

Abstract: There are various abnormal phenomena before the earthquake, and how to effectively extract exception information before the earthquake is a very important research topic. The geometric moving average martingale algorithm based on sliding window was proposed to extract the anomaly features before earthquake. The seismic data were processed by geometric moving average martingale and sliding window feature extraction, and the anomaly features of earthquake could be effectively extracted before earthquake. Through the analysis of the NOAA (National Oceanic and Atmospheric Administration satellite outgoing long wave radiation information before the Wenchuan earthquake and Lushan earthquake, the experiments show that the algorithm can detect that the earthquake area is more obviously abnormal than the surrounding area. This anomaly can help researchers determine earthquake area before the earthquake.

Key words: sliding window, geometric moving average martingale, earthquake, anomalies analysis, feature exaction

中图分类号:

TP311

陈丽萍孔祥增郑之林新棋詹晓珊. 基于滑动窗口的几何移动平均鞅算法在震前异常分析中的应用[J]. 计算机应用, 2013, 33(12): 3608-3610.

CHEN Liping KONG Xiangzeng ZHEN Zhi LIN Xinqi ZHAN Xiaoshan. Application of geometric moving average martingale algorithm in anomaly analysis before earthquake based on sliding window[J]. Journal of Computer Applications, 2013, 33(12): 3608-3610.

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基于滑动窗口的几何移动平均鞅算法在震前异常分析中的应用

Application of geometric moving average martingale algorithm in anomaly analysis before earthquake based on sliding window

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