Intermediate-term Predictions of Earthquakes in Italy: Algorithm M8

—Large earthquakes in Italy are preceded by a specific seismic activation which could be diagnosed by a reproducible intermediate-term earthquake prediction method—a modification for lower seismic rate areas of the algorithm, known as M8 (Keilis-Borok and Kossobokov, 1990). Use has been made of the PFG-ING catalog of earthquakes, compiled on a regular basis, to determine areas and times of increased probability for occurrences of M≥ 6 earthquakes. In retroactive simulation of forward prediction, for the period 1972–1995, both the 1976 Friuli, M = 6.1 and the 1980 Irpinia, M = 6.5 earthquakes are predicted. In the experiment where priority magnitude scale is used, the times of increased probability for a strong earthquake to occur (TIPs) occupy less than a quarter of the total magnitude-space-time domain, and are rather stable with respect to positioning of circles of investiga tion. Successful stability tests have been made considering a recently compiled catalog (CCI97) (Peresan et al., 1997). In combination with the CN algorithm results (Costa et al., 1996) the spatio-temporal uncertainty of the prediction could be reduced to 5%. The use of M8 for the forward prediction requires the computations to be repeated each half-year, using the updated catalog.     

Recent development of the earthquake strong motion-intensity catalog and intensity prediction equations for Iran

This study aims to develop a new earthquake strong motion-intensity catalog as well as intensity prediction equations for Iran based on the available data. For this purpose, all the sites which had both recorded strong motion and intensity values throughout the region were first searched. Then, the data belonging to the 306 identified sites were processed, and the results were compiled as a new strong motion-intensity catalog. Based on this new catalog, two empirical equations between the values of intensity and the ground motion parameters (GMPs) for the Iranian earthquakes were calculated. At the first step, earthquake “intensity” was considered as a function of five independent GMPs including “Log (PHA),” “moment magnitude (M_W),” “distance to epicenter,” “site type,” and “duration,” and a multiple stepwise regression was calculated. Regarding the correlations between the parameters and the effectiveness coefficients of the predictors, the Log (PHA) was recognized as the most effective parameter on the earthquake “intensity,” while the parameter “site type” was removed from the equations since it was determines as the least significant variable. Then, at the second step, a simple ordinary least squares (OLS) regression was fitted only between the parameters intensity and the Log (PHA) which resulted in more over/underestimated intensity values comparing to the results of the multiple intensity-GMPs regression. However, for rapid response purposes, the simple OLS regression may be more useful comparing to the multiple regression due to its data availability and simplicity. In addition, according to 50 selected earthquakes, an empirical relation between the macroseismic intensity (I₀) and M_W was developed.     

地震与核爆识别的小波包分量比方法

频谱分析法在核爆与地震识别中具有广泛的应用．但是频谱分析方法是稳态方法,即使采用Gabor变换,也因时-频窗口形状不变而分辨串较低．为提高时-频分辨率,本文将小波变换理论用于乌鲁木齐台记录的地震与核爆事件的分析,并提出了识别核爆和天然地震的小波包分量比判据．通过对加拿大黄刀地震台记录的印度地下核爆的分析,进一步验证了小波包分量比判据对核爆和地震的识别具有较高的识别效率．结果表明：对于地震信号,其小波包分量比U03/U1一般都大于1.0,而对于核爆信号,比值U03／U13一般都小于1.0.     

华北地区中强震前中小地震活动的动态演化特征研究

应用地震活动加速指数AI算法对华北地区1970年以来M_L≥6.0地震进行了回溯性研究。 利用该方法统计中强震前的中小地震活动频度, 分析结果显示在空间上能够反应出中小震活动频度的异常。 另外, 应用有关地震活动的频度面积S值方法, 对M_L6.0级以上强震前后的中小地震活动在时间分布上进行了研究, 此方法对AI算法的计算结果在时间上给予了支持。 结果表明: AI指数能够量化地给出中强震前中小地震活动的相对增强或减弱程度, 中强震的S值在震前表现为高值或低值异常, 震后下降或上升。 S值的异常点与AI扫描值的异常结果在时空分布上相辅相成。 在地震目录完整的情况下, 中强震震中区及其附近地区震前1 a的中小地震活动与之前3 a、 5 a的活动背景相比, 出现明显的“加速”或“减速”现象。 利用这两个参量的变化, 可为该地区中强震的预测分析提供一定的判定指标。     

应用统计物理方法分析川滇地区地震危险性

川滇菱形块体及其边界断裂带(21°～33°N,96°～108°E)是中国大陆地震活动最强烈的地区之一,该地区发生的一系列大地震造成了巨大的人员伤亡和财产损失。文中分别应用基于地震空间相关性和地壳形变场的预测方法分析了该地区未来的地震危险性。由Kagan等(1994)提出的基于地震空间相关性的方法,假定未来发生地震的概率与历史发生地震的频度成正比,根据历史地震目录建立统计学模型估计未来发生地震的概率。回溯性检验表明,这种方法对于评估地震复发周期较短的断裂带的地震危险性有较高的有效性,但对于地震复发周期较长的断裂带,如龙门山断裂带,很难给出一个理想的预期。由Shen等(2007)提出的基于地壳形变场的方法,假定长期地震危险性与地壳构造应变率成正比,根据由GPS观测获得的应变率场建立统计学模型评估未来的地震危险性。回溯性检验表明,川滇地区过去30a间发生的地震与区域应变率的大小没有明显的对应关系,但过去500a间发生的地震与应变率场有很高的相关性,表明由10a时间尺度的大地测量资料得到的地壳应变场可以很好地反映数百a时间尺度的地震危险性。     

Seismicity Factor A-Value and Its Application to Mid-Term Earthquake Prediction in North China

The seismicity factor A-value is defined by synthesizing the seismicity precursors in time, space and magnitude in this paper. The seismicity data of moderate or small earthquakes during 1972 ~ 1996 in North China are used to perform spacial scanning of seismicity factor A-value. The result shows that there are obviously anomaly zones of A-value with better prediction effect in the mid-term of 2~3 years before most moderately strong earthquakes. Some problems regarding the mid-term prediction using A-value have been discussed.     

Application of mechanical and statistical models to the study of seismicity of synthetic earthquakes and the prediction of natural ones

Based on a cellular automata model, which obeys rules produced by a spring-damper-slider model of fault network, a synthetic earthquake catalog of deterministic chaos can be produced. It is a challenge to inverse the model parameters and predict the synthetic earthquakes from the synthetic catalog. We apply an improved statistical model of coupled stress release to the synthetic catalog, it does successfully inverse the stress evolution of the system, but effectively prediction of the earthquakes from the stresses remains a problem. This research is partially supported by the Chinese Joint Seismological Science Foundation and Asian 2000 Foundation of New Zealand.     

京西北盆岭构造区强震复发概率模型及地震潜势的定量评估

基于京西北盆岭构造区活动构造的定量化研究成果 ,视强震复发间隔为一随机变量 ,借鉴NB模型的建模方法 ,结合强震复发过程中存在分形规律的思想 ,建立京西北模型———强震复发间隔的均一化值服从正态分布N(1.0 0 0 3,0 .2 4 6 4 2 ) ;京西北盆岭构造区未来可能发生地震概率较高的断裂是 :天镇 -阳高盆地北缘断裂、阳原盆地南缘断裂、延庆盆地北缘断裂辛韩段、矾山盆地北缘断裂燕水段、宣化盆地南缘断裂     

长短时记忆神经网络在中期地震预报中的探索——以川滇地区为例

利用机器学习方法对地震活动大数据进行挖掘,识别出一些过去认识不到的异常,提高地震预测的准确性,是一个非常具有挑战性的科学问题.本文基于川滇部分地区（24°N—32°N,98°E—106°E）地震目录,采用滑动的时空窗口,选取16个反映地震时空强度分布特征的地震预测因子,建立了长短时记忆（LSTM）神经网络,对研究区域9个子区块未来一年的最大地震震级进行预测.通过设置训练集：测试集=8：2和训练集：测试集=7：3两个不同的训练测试模型,对过往发生的地震进行了回溯性预报.结果表明：训练集：测试集=7：3模型能够利用1970年1月至2004年9月的地震目录进行学习,成功回溯性预报2008年汶川地震;训练集：测试集=8：2模型利用1970年1月至2009年5月资料进行训练,回溯性预报2010—2019年间6级以上地震的R评分为0.407,回溯性7级地震预报时准确率高达92.31%.本文还探讨性给出预测意见：2022年2月前研究区西部、中部、东部、西南部存在发生5.1~5.3级地震的潜在危险性.

     

云南地区波速比预报效能的动态分析

通过对云南地区１０多年来地震波速比资料进行研究和应用,对波速比异常的预报效能作了动态分析,异常对应地震的时间,距离,幅度均随强震的孕育和强震活跃期的盛衰过程而演变。短临虚报异常可能提供强震孕育的中长期信息和中强震的中长期源兆。研究结果表明,其漏报的地震是发生在２５０ｋｍ范围内的后续（３个月内）中强地震;对发生在１００ｋｍ范围内的中强震（强震前５个月）有对应,而３００ｋｍ外的中强震漏报。     

Discussion on Amending and Compiling the Historical Earthquake Catalogue

In this paper, some opinions related to amending and compiling the historical earthquake catalog are proposed. They include the following points: (1) the catalog should be based on historically recorded facts; (2) we should consider the accuracy that could actually be attained through the use of historical earthquake data; (3) emphasis should be placed on field survey of historical earthquakes; (4) use engineering seismology and earthquake prediction to develop research in historical earthquakes.     

2013年甘肃岷县漳县M_S6.6地震余震序列时域衰减特征分析

本文基于补充遗漏地震事件后的地震目录和修正的大森公式,对2013年7月22日甘肃岷县漳县6.6级地震余震序列时间域衰减特征进行了分析.鉴于主震后短时间内目录遗漏的余震较多,首先利用岷县台连续地震记录波形的高频包络差,检测主震后3h内目录遗漏的地震.经检测在主震后3h内共发现目录遗漏的ML1.0以上地震139个,最大震级为ML3.6.主震后1000s内检测到遗漏地震69个,约为目录给出余震数量的6倍.而后使用补充遗漏地震的目录,基于修正的大森公式分别拟合余震频度和余震地震矩随时间的变化.结果显示拟合p值约为1.07,表明岷县漳县地震余震序列衰减速率与全球平均水平接近,而未补充遗漏地震的频度拟合会造成余震序列衰减速率的低估.利用高频包络差直接计算地震频度曲线,通过三种衰减模式对地震频度曲线拟合参数比较,未观察到岷县漳县地震主震后存在早期余震缺失现象.分析认为,加入遗漏地震可以提高余震频度拟合估计衰减速率结果的准确度和精度,若缺少遗漏地震检测结果,则使用地震矩拟合所得衰减速率结果准确度较优,但需充分考虑其精度上的误差.在分析余震序列衰减特征的实际研究工作中,需根据地震目录完整性选择适当的拟合方法.     

安徽及周边地区小爆破的识别与判据研究

根据安徽测震台网记录的爆破与地震的数字资料,采用波谱分析方法,对该区域记录的小爆破与小震级地震事件计算纵横波拐角频率和卓越周期,试图获得爆破和地震识别的定量指标。对比研究波谱特征,发现爆破与地震的纵横波拐角频率和卓越周期等存在明显差异,为该地区小爆破的识别,提供了新的判据。最后,对爆破与地震其他方面的判据特征进行了总结。     

大地电流与电离层负电异常预报地震的可能性

在地球及其电离层的静电理论的范畴内,能简单地解释一切跟地震有关的电气现象。电离层由于电子的康普顿散射通常是正电的,地球深部由于电子静电泵离电离层也是正电性的。这些电于形成约1800安的规则连续电流,而正离子必然是突发式流动而形成雷电、火山喷发以及某些类型的地震。地震的主要成因显然是构造应力的释放,但是地震目录中的某些地震可能是被静电爆发作用所触发的。这种地震具备下列两个必要条件:位于深处的正离子能贯穿高电阻的上地幔;在电离层中存在吸引正离子的局部负电异常。大气层电场和“地震—大地电流”的同步联测可能是预报地震的时间和地点的两单而又准确的方法。     

Recognition of earthquake-prone areas: Methodology and analysis of the results

We present the results of verifying the areas that were detected as prone to strong earthquakes by the pattern recognition algorithms in different regions of the world with different levels of seismicity and, therefore, different threshold magnitudes demarcating the strong earthquakes. The analysis is based on the data presented in the catalog of the U.S. National Earthquake Information Center (NEIC) as of August 1, 2012. In each of the regions considered, we examined the locations of the epicenters of the strong earthquakes that occurred in the region after the publication of the corresponding result. There were 91 such earthquakes in total. The epicenters of 79 of these events (87%) fall in the recognized earthquake-prone areas, including 27 epicenters located in the areas where no strong earthquakes had ever been documented up to the time of publication of the result. Our analysis suggests that the results of the recognition of areas prone to strong earthquakes are reliable and that it is reasonable to use these results in the applications associated with the assessment of seismic risks. The comparison of the recognition for California with the analysis of seismicity of this region by the Discrete Perfect Sets (DPS) algorithm demonstrates the agreement between the results obtained by these two different methods.     

基于最近邻支撑向量特征线融合算法的核爆地震识别

为增强核爆地震模式分类器的泛化能力以提高对核爆炸事件的准确识别能力,论文提出了一种选择支撑向量样本集来表征训练样本集的最近邻支撑向量特征线分类算法,用以训练时扩展核爆地震的训练样本库,提高分类器的泛化能力.该算法用于核爆炸和地震的识别结果发现,和最近邻特征线分类器相比,提出的算法降低了计算复杂度,但识别能力却有些许降低.对新算法的分析发现,纯粹的支撑向量集不能完全代表原始样本空间集,支撑向量比例在其中有重要作用,为发挥支撑向量比例的作用以提高核爆分类器的识别能力,提出了最近邻支撑向量特征线融合算法.最后以核爆地震数据库对上述算法进行了检验和分析,理论分析和识别结果证实,在相同的训练样本选择条件下,最近邻支撑向量特征线融合算法对于核爆炸的识别来说具有较好的泛化能力,正确识别率达到90.3%,且优于支持向量机算法和最近邻特征线算法.     

基于克隆选择原理的核爆地震特征选择方法

为了解决核爆地震自动识别中最优特征子集的选择问题,根据克隆选择原理,提出了一种过滤与封装相结合的特征选择方法.该方法融合了封装式与过滤式特征选择方法的优点,利用局部化的类别可分性判据来处理核爆地震样本的多峰分布问题,通过设定独立的记忆抗体能够保证最终结果是搜索过的最佳特征组合,并且可以处理设定和不设定最优特征子集维数两种情况下的特征选择问题.首先通过UCI数据集中呈多峰分布的玻璃数据验证了该特征选择方法的有效性,进而将其应用到核爆地震特征选择中.核爆地震特征选择实验结果表明,该方法不仅有效地降低了特征空间的维数,而且使分类精度提高了2个百分点,与封装式特征选择方法相比,该方法的计算复杂度大为降低.     

Diurnal periodicity of earthquakes in Greece

The catalog of earthquakes that happened in Greece over the period of 1964 to 2008 was used for the analysis of their diurnal periodicity in this region. The quality of the catalog was examined with the defining of the representativeness levels of earthquakes in different selections. The earthquakes, including relatively strong events with the magnitude M ≥ 4.0, demonstrate diurnal periodicity with seasonal differences in their course reflected in their higher summer seismicity as compared with the winter one.     

Seismicity of the North of the Russian Plate: Relocation of Recent Earthquakese

The hypocenters of the earthquakes recorded in the north of the Russian Plate from 1982 to 2013 are relocated. The relocation of the hypocenters is based on the common velocity section, common methodology, and the entire set of the initial data and bulletins available from the Russian and foreign seismic stations. The efficiency of the algorithm for calculating the hypocentral parameters and the velocity section is demonstrated by the example of two nonmilitary nuclear explosions in July 18, 1985 and September 6, 1988 in the northern part of the European Russia. For the first time, two earthquakes of July 19, 1982 and October 7, 2012, which have not been previously reported in the catalogs for the north of the Russian plate, are included in the seismic catalog.     

滇西北东条带地震围空及条带与中强地震的时空关系

利用1970年1月1日至2008年12月31日云南省地震遥测台网记录的地震目录,对中强以上地震进行余震删除。利用已删除余震的正式目录,研究滇西北东条带中强地震前地震空区及条带的分布情况。1970年以来滇西北东条带共发生31组5.0级以上地震,其中19组地震前存在地震空区、条带现象,占61%。中强地震发生地点与地震前空区、条带分布区域密切相关,在其内部或边缘区域。中强震发生时间与空区和条带结束时间相关,在其结束后半年内发震,对地震短临预测具有一定实际意义。