CUSUM 算法在 NOAA 卫星数据震前异常分析中的应用

摘要

Abnormal information before earthquake can help researchers detect earthquake.In this paper we use CUSUM (cumulative sum)algorithm as a data mining tool to detect seismic anomalies on OLR (outgoing longwave radiation)data.The main steps include sum cumulating,curve smoothing,feature points extracting and characteristic curve outputting.According to the study and analysis on outgoing longwave radiation information of NOAA satellite in regard to Wenchuan earthquake and Argentina earthquake covering a whole year’s data before and after the earthquake,it is found that the anomaly happens before the earthquake,and its degree changes from small to large until the maximum value right around the occurrence of earthquake;after the earthquake the anomaly degree gradually diminishes.Experimental results show that the proposed method is feasible and effective.%震前异常信息可以帮助研究人员检测地震。将 CUSUM（cumulative sum）算法作为一种数据挖掘的工具，对射出长波辐射 OLR（outgoing longwave radiation）数据进行地震异常检测。主要工作包括计算累积和、平滑曲线、提取特征点和输出特征点曲线。通过对汶川地震、阿根廷地震前后一整年的 NOAA 卫星射出长波辐射信息进行研究分析，发现异常发生在地震之前，且异常度由小及大，到地震前后达到异常度最大；地震结束后，异常度逐渐减小。实验结果表明，该方法是可行的，有效的。