摘要
中强地震发生前存在地表异常增温现象,热红外信息可以成为地震短临预测的途径之一.然而,地震预测研究常存在可供分析的震例样本不足的问题.本文基于MODIS地表温度数据,先通过深度卷积生成对抗网络(DCGAN)对地震前的地温数据做扩增处理,再将扩增后的地温数据输入深度残差收缩网络进行特征提取并预测未来短期内是否存在发生5级及以上地震事件的可能性.实验针对中国地震较多的中西部地区,将地表温度数据依照地震实际发生情况标记为发生地震数据和未发生地震数据,样本比为3:1,分不同的预测时间段进行比较.结果显示,5日预测的准确率最高为73.86%,正确预测发生占实际发生的比例为68.09%.多次实验准确率曲线趋向稳定,证明该预测方法有很好的实用性.基于MODIS数据结合数据扩增与残差收缩网络的预测方法为短临中强地震预测研究提供了一种新思路.
Anomalies of temperature increase will occur before moderate and strong earthquakes,and thermal infrared information can be one of the ways to predict the short-term and imminent earthquakes.However,earthquake prediction research often has the problem of insufficient earthquake samples for analysis.Based on the MODIS surface temperature data,the deep convolutional generative adversarial network(DCGAN)is used to amplify the pre-earthquake ground temperature data,and then the amplified ground temperature data is input into the deep residual shrinkage network for feature extraction,and predict whether there is the possibility of M≥5 earthquake in the short-term future.The experiment is aimed at the central and western regions of China where earthquakes often occur,and the surface temperature data is marked according to the actual occurrence of the earthquake as the data of the occurrence of earthquakes and the data of no earthquakes.The sample ratio is 3:1,and the comparison is divided into different prediction time periods.The results show that the highest accuracy rate of 5-day prediction is 73.86%,and the proportion of correct predictions to actual occurrences is 68.09%.The accuracy rate curve of multiple experiments tends to be stable,which proves that the prediction method has good practicability.Based on MODIS data,the prediction method combining data augmentation and residual shrinkage network provides a new idea for short-term,moderate-strong earthquake prediction research.
作者
张翔
孙宪坤
胡峻
尹京苑
熊玉洁
ZHANG Xiang;SUN Xian-kun;HU Jun;YIN Jing-yuan;XIONG Yu-jie(School of Electronic and Electrical Engineering,Shanghai University of Engineering and Science,Shanghai 201620,China;Earthquake Administration of Shanghai Municipality,Shanghai 200062,China)
出处
《地震》
CSCD
北大核心
2022年第2期74-88,共15页
Earthquake
基金
国家重点研发计划项目(2019YFC1509202)
国家自然科学基金项目(62006150)
上海青年科技英才扬帆计划项目(19YF1418400)
关键词
地震预测
MODIS
数据扩增
深度卷积生成对抗网络
深度残差收缩网络
Earthquake prediction
MODIS
Data augmentation
Deep convolution generation adversarial network
Deep residual shrinkage network
