对1989年大同－阳高地震序列两次强余震发震时间的灰色预测

应用灰色系统理论对１９８９年大同－阳高６．１级地震序列两次强余震（系指Ｍ＿Ｌ≥４．７）的发震时间进行了尝试性预测，其结果与事实比较吻合，表明该方法在震后短时间内，用仅有的部分序列资料来估计其发展趋势，具有一定的实际意义。     

华北地区中强地震发生时间的预测研究

通过对华北地区中强地震（指Ms≥5．5的地震）发生时间不均匀性的研究结果表明：自1815年以来，该区可划分为5个中强地震集中活跃时段。可用灰色系统理论和方法建立灰色预测模型。预测未来一个活跃时段的起止时间。如果发生在活跃时段内的中强地震的发生时间呈较好的线性趋势变化，则可用二指数平滑方法进行预测。在此基础上，本文还对它的预测精度作了估计。     

1993年8月份华北的M＿L≥3．0地震

１９９３年８月份华北的Ｍ＿Ｌ≥３．０地震华北地区（３３°—４２°Ｎ，１１１°—１２５°Ｅ）１９９３年８月共发生９次的Ｍ＿Ｌ≥３．０地震，其中最显著的事件是１９９３年８月３０日大同发生的Ｍ＿Ｌ４．１地震。继上月山西带南端曲沃地区发生Ｍ＿Ｌ４．１地震后，...     

南黄海6.1级地震的灰色预测

曾用灰色系统方法预测１９９６年全年的地震趋势。本次南黄海Ｍｓ６．１级地震的发生表明震级和时间的预测效果较好，因而认为作为一种手段，灰色系统方法可以加入地震综合预报的行列。     

M≥6．0级强震后有无M≥5．0级地震的模糊聚类分析

在充分了解地震序列特征的基础上，从不同角度的物理背景选出２６项地震序列的原始特征。根据这些原始特征的Ｗａｌｌｅｎ评分，精选出１１项能突出表现地震序列的特征参数作为指标，采用ＩＳＯＤＡＴＡ模糊聚类方法对地震序列进行分类，在分类过程中，将地震序列分为两类：Ｉ类为Ｍ≥６．０级强震后三个月内还有震级为Ｍ≥５．０级的强震发生；Ⅱ类为Ｍ≥６．０级强震后三个月内无Ｍ≥５．０级的地震。在一次强震发生后，短期内还有没有另一次强震？这是大震现场分析预报工作中最重要、最迫切的问题之一。这一问题的解决，实际上就是在强震发生后的短时间内，对地震序列的类型作出判断。人们已研究过不少判别地震序列类型的方法，如ｈ值、ｂ值、等待时间，Ｋ值等。这些方法大多需要震后积累一定时段的序列资料才能满足应用条件，而震后趋势判断又是一项十分迫切的任务。为了使地震序列类型的划分具有预报价值，我们已作了一些有意义的工作，曾利用一次中强以上地震（Ｍ＿ｏ≥４．７）发生后头三天地震序列资料，应用模式识别、模糊数学方法对未来三个月内是否可能发生相当（Ｍ＝Ｍ＿ｏ±０．３）或更大（Ｍ＞Ｍ＿ｏ）地震作过综合判定。本文在此基础上用模糊聚类的ＩＳＯＤＡＴＡ方法对此问题作一具体     

1994年9月首都圈M＿L≥2．0地震动态

１９９４年９月首都圈Ｍ＿Ｌ≥２．０地震动态１９９４年９月份在首都圈（３８．０°─４１．０°Ｎ，１１３．０°─１２０．０°Ｅ）范围内，共发生Ｍ＿Ｌ≥２．０以上地震１１次，其中最为显著的是９月９日发生在河北卢龙Ｍ＿Ｌ≥３．２地震（见下表）。本月发生的２级...     

大同地震后华北地震形势

采用几种方法分析了大同地震后华北地区的地震形势。根据地震活动和构造特征划分了研究区域，用作者提出的灰色线性预测模型及可公度性预测了发震时间，用作者提出的多点测位法预测了地震危险区并用近百年大陆地震活动特征估计了震级。综合分析结果认为，１９９５～１９９６年华北发生ＭＳ≥５．５地震的概率为Ｐｔ｛１９９５～１９６６｝＝７／１１～８／１１，地震危险区位于晋东南的概率为ＰＳ＝７／８～１。     

更新论在估计西南地区未来地震活动中的应用

更新过程在许多领域已有应用。本文检验确认四川省、云南省Ｍ＿ｓ≥５．５，６．０，６．５；川滇Ｍ＿ｓ≥６．０、６．５，７．０；西藏Ｍ＿ｓ≥６．０，６．５，６级地震（主震）间隔时间分别都可认为服从指数分布；同时其中大多又可认为服从对数正态分布，分别对未来１年、３年、５年给出地震发生的概率，并对以上时段内可能发震的次数作出估计，对西南地区未来几年内的地震活动强度给出简明的统计描述，应注意：年内四川省应有Ｍ＿ｓ≥５．５级地震发生，且震级可能大于或等于６．０级。     

1993年9月份首都圈地区M＿L≥2．0级地震

１９９３年９月份首都圈地区Ｍ＿Ｌ≥２．０级地震１９９３年９月份在首都圈（３８．０°—４１．０°Ｎ，１１３．０°—１２０．０°Ｅ）范围内，共发生１７次Ｍ＿Ｌ≥２．０地震，其中１２次２—２．９级地震，５次Ｍ＿Ｌ＞３的地震。震级最大的一次为９月２７日发生在...     

六级以上强震后半年内有无五级以上地震的模糊聚类分析

根据３６个初选问题的Ｗａｌｌｅｎ评分，精选出１０项能突出表现地震序列的特征参数作为指标，采用ＦＣＭ模糊聚类方法对地震序列进行分类，在分类过程中，将地震序列分为两类：Ｉ类为Ｍ≥６．０强震后六个月内还有震级为Ｍ≥５．０的强震发生；Ⅱ类为Ｍ≥６．０强震后六个月内无Ｍ≥５．０地震。以中国大陆地区１９９６年以来的２６次Ｍ≥６．０强震序列建立震后判别模型，然后以近期发生的８次强震序列进行了外推检验。     

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。     

Diagnosis of Time of Increased Probability (TIP) for Volcanic Earthquakes at Mt. Vesuvius

The possibility of intermediate-term earthquake prediction at Mt. Vesuvius by means of the CN algorithm is explored. CN was originally designed to identify the Times of Increased Probability (TIPs) for the occurrence of strong tectonic earthquakes, with magnitude M ≥ M₀, within a region a priori delimited. Here the CN algorithm is applied, for the first time, to the analysis of volcanic seismicity. The earthquakes recorded at Mt. Vesuvius during the period from February 1972 to June 2004 are considered, and the magnitude threshold M₀ selecting the events to be predicted is varied within the range: 3.0–3.3. Satisfactory prediction results are obtained, by retrospective analysis, when a time scaling is introduced. In particular, when the length of the time windows is reduced by a factor 2.5–3, with respect to the standard version of CN algorithm, more than 90% of the events with M ≥ M₀ occur within the TIP intervals, with TIPs occupying about 30% of the total time considered. The control experiment ``Seismic History' demonstrates the stability of the obtained results and indicates that the CN algorithm can be applied to monitor the preparation of impending earthquakes with M ≥ 3.0 at Mt. Vesuvius.     

Time distribution characteristics of regional macroseismic activity in the Sichuan-Yunnan region and its significance to mid-long term prediction

IntroductionThe development and occurrence of macroseismic activity come from the specific structUreenvironment and stress condition. So the space-time distribUtion of strong quakes appears to bevery inhomogeneous. Earthquakes with Ms27.0 in a seismicity period presented often a speeding-up pattern with time in different seismic provinces. That is, the cumulative frequency of earthquakes with Ms27.0 increase with exponent N(t)=ae', in a seismicity period (ZHANG, FU, 1989).It means that t…     

TIP方法在大华北地区预报效能的研究

用改进的Ｍ８算法研究了１９７９年以来大华北地区存在的ＴＩＰ，即强震发生概率增长时间，结果表明８次中强震有７次发生在被判定为概率增长时间内，ＴＩＰ警戒占研究总时空域的４０．７％，Ｒ评分为０．４６８。获得了较好的中强震中期预测内符效果，表明该方法可作为大华北地区中强震中期预报的手段之一。     

Rediscussion on the seismic regime network

ＲｅｄｉｓｃｕｓｓｉｏｎｏｎｔｈｅｓｅｉｓｍｉｃｒｅｇｉｍｅｎｅｔｗｏｒｋＺｅ－ＧａｏＷＡＮＧ（王泽皋）；Ｐｅｉ－ＱｉｎｇＳＵＮ（孙佩卿）；Ｊｉｎｇ－ＣｈｕｎＧＡＯ（高景春）；Ｓｈｕ－ＬｉａｎＬＩ（李淑莲）；ＸｕｅＺＨＡＮＧ（张雪）ａｎｄＹａｎＧＵＯ...     

Periodic spectral characteristics of seismicity before strong earthquakes and their application

IntroductionMaximumentropyspectralmethod(MEM)(Burg,1972)hadbeenamethodusuallyusedinstudyingtheseismicityanditsmainpurposeistofindthedominantspectrainthelong-termseismicityprocessesinthepastyears(Zhu,1985).Inthispaper,themethodisappliedtostudywhethertherearesomespecialspectraofseismicityinsomespecificstagesinearthquake-generatingprocesses.Sowestudyseparatelythenormalandabnormalstageofearthquakeactivity,whoseactiveprocessisregardedasstablestochasticprocess,inordertofindtheirspectracharactersan…     

Regularities in the time variations of seismic parameters and their implications for prediction of strong earthquakes in Greece

Time variations in the parameters of seismic activity in two regions in Greece, which are known to have different geodynamical conditions, are analyzed using the FastBEE algorithm suggested in (Papadopoulos and Baskoutas, 2009). The study is based on the data on weak earthquakes that occurred in two local regions. One region pertains to the zone dominated by intensive compression stress field, while another is located in the region of a relatively lower intensity extension stress field. It is shown that in the zone of compression the seismic parameters exhibit anomalous temporal behavior before strong earthquakes with Ms ≥ 5.7, whereas in the zones of extension, similar anomalies precede earthquakes with lower magnitudes of up to Ms ≥ 4.9. The most informative parameters for the purposes of predicting strong seismic events are the released seismic energy in the form logE ^2/3 and the slope of the frequency-magnitude dependence, b-value. The seismic activity in the region, expressed in terms of the logarithmic number of earthquakes, per unit time in some cases does not exhibit any particular pattern of behavior before strong earthquakes. In the time series of the studied parameters, four stages in the seismic process are clearly distinguished before strong earthquakes. Typically, a strong earthquake has a low probability to occur within the first two stages. Instead, this probability arises at stage III and attains its maximum at the end of this stage coinciding with the occurrence of the strong earthquake. We suggest these features of the time series to be used for the assessment of seismic hazard and for the real-time prediction of strong earthquakes. The time variations in the b-value are found to be correlated with the time variations inlogE ^2/3. This correlation is closely approximated by the power-law function. The parameters of this function depend on the geodynamical features of the region and characterize the intensity and the type of the regional tectonic stresses. The results of our study show that the FastBEE algorithm can be successfully applied for monitoring seismic hazard and predicting strong earthquakes.     

孟连7.3级强震短临预报研究--应用"层次法"的模拟预测

孟连7.3 级大震前有中强地震发生,这对大震的地点预报十分有利,但中、强震发生后是否一定有大震发生,这仍然是预报难题.其次,中、强震发生后,究竟相隔多长时间后发生大震,这是另一个预报难题.以孟连地震作为震例,用"层次法"对上述二个问题作出回答.最后由"层次法"得到孟连地震的预报参数为:震中22°N,99°E;MX 7 .3;时间1995年7月12日.预测参数与实际地震参数一致.     

Consistent CMT solutions from Harvard University before great earthquakes in Kurile Islands and its significance for earthquake prediction

Introduction In the development of seismic science,the improvement of observational instruments is prone to produce new parameters and promote rapid growth of seismology.For example,after the global digital seismograph network is established,some studies that could not be made or easily made in the past are now being carried out successively.As a result,analytical studies based on digital data have been made one after another and digital seismology has formed.Up to now,Harvard University has …