地震前后射出长波辐射信号的异常检测系统  

Detection System for Abnormal Long Wave Radiation Signals before and after Earthquakes

作　　者：薛盛杰 林岭[1] XUE Shengjie;LIN Ling(College of Computer and Cyber Security,Fujian Normal University,Fuzhou,China,350117)

机构地区：[1]福建师范大学计算机与网络空间安全学院,福州350117

出　　处：《福建电脑》2023年第10期10-15,共6页Journal of Fujian Computer

摘　　要：为了更好地分析地震前后射出长波辐射异常变化情况与地震发生的联系,减小地震所带来的人员伤亡及财产损失,开发一个地震异常检测分析系统是十分必要的。本文基于数据挖掘及鞅理论异常识别的结合算法,开发了一个基于地震前后射出长波辐射信号的异常检测系统。该系统通过K-means聚类算法及概率模型对射出长波辐射数据进行特征提取,并对其中异常数据进行挖掘和识别,分析其在地震前后异常变化情况。实践结果表明,地震前后,射出长波辐射数据在时间及空间两个维度均会出现异常变化,采用该系统可以在一定程度上对地震的发生起到预测作用。In order to better analyze the relationship between the abnormal change of outward longwave radiation before and after the earthquake and the occurrence of the earthquake,and to reduce the casualties and property losses caused by the earthquake,it is necessary to develop a seismic anomaly detection and analysis system.Based on the combination of data mining and martingale theory,a seismic analysis detection system is developed in this paper,which extracts the features of outward longwave radiation data by K-means clustering algorithm and probability model,the anomaly data are mined and identified,and the anomaly variation before and after the earthquake is analyzed.The practical results show that the outgoing long wave radiation data before and after the earthquake will change abnormally in both time and space dimensions,and the system can be used to predict the occurrence of earthquake to a certain extent.

关 键 词：射出长波辐射 数据挖掘 鞅理论 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]