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基于形变数据共享,建立跨区域联动观测模型,可在孕震异常发生时确认异常范围.通过2010年7月9日两次如东近海地震前异常分析,结果表明,多套以上倾斜联动观测能监测到孕震异常的发生区域,从而为震前预报确认震中提供更多的方位信息. 相似文献
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本文研究了神经网络方法在基于地震活动性指标的中短期地震预报和基于非测震学前兆异常从属函数的短期地震预报中的应用。选用含一个或两个中间层的前向神经网络模型，并采用与之相适应的ＢＰ算法。以华北地区多年的地震活动性资料和首都圈及其邻近地区的短水准、地电阻率、地磁总强度、水位、水氡含量等前兆观测手段的８０余个台项的多年测资料为基础，对神经网络方法以上两方面的应用作出了实际计算、分析与检验。对一些大地震的发 相似文献
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This paper proposes the use of neural networks to predict damage due to earthquakes from the indices of recorded ground motion. Since the relationship between ground motion indices and resulting damage is difficult to express in mathematical form, neural networks are conveniently applied for this problem. Simulated earthquake ground motions are used to have a well-distributed data set and the ductility factor from non-linear analysis of two single-degree-of-freedom structural models is used to represent the damage. A sensitivity analysis procedure is described to identify qualitatively the input parameters that have a greater influence on the damage. The result of the trained neural network is then verified by using several recorded earthquake ground motions. It is found that some instability in the prediction can occur. Instability occurs when input values exceed the range of the training data. The neural network model using PGA and SI as input give the best performance in the recall tests using actual earthquake ground motion, demonstrating the usefulness of neural network models for the quick estimation of damage through earthquake intensity monitoring. 相似文献
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本文以西昌台阵观测的8 321次近震数据为例,详细介绍了利用深度卷积神经网络检测地震的数据处理流程,包括数据预处理、模型训练、波形长度、网络层数、学习率和概率阈值等关键参数对检测结果的影响,并将训练得到的最优模型,应用于事件波形和连续波形的检测。研究表明,数据预处理和数据增强可以提升模型的检测精度和抗干扰能力。用于模型训练的波形窗口长度可近似于S-P到时差的最大值。不同网络层数（5—8层）的检测结果差别不大。对于地震检测,学习率设为10?4—10?3较为合适。卷积神经网络检测出的地震数量与选择的概率阈值有关,通过绘制精确率-召回率变化曲线,可以为选择合适的概率阈值提供参考。本文为进一步利用深度学习算法提高地震检测效果提供了参考。 相似文献
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准时间可预报复发行为与断裂带分段发震概率估计 总被引：7，自引：0，他引：7
反不确定性引入“时间可预报模式”，可将一次地震之后的平静时间表示成与这次地震位错量在小呈正相关的随机变量。称这种带有不确定性的地震原地复发行为为“准时间可预报行为”。对于历史地震资料，准时间可预报复发行为可由地震后平静时间的对数与地震烈度的回归方程。文中给出了估计一条枯断裂带不同段落以上一次地震烈度值为背景的平均复发时间间隔的方法，以及可用 于对未来地震潜势进行不确定评价的实时概率模型，并以鲜水河 相似文献
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SEISMO-GEOLOGICAL SIGNATURES FOR IDENTIFYING M≥7.0 EARTHQUAKE RISK AREAS AND THEIR PREMILIMARY APPLICATION IN MAINLAND CHINA 
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下载免费PDF全文 High-magnitude earthquake refers to an earthquake that can produce obvious surface ruptures along its seismogenic fault and its magnitude M is at least equal to 7.0. Prediction and identification of locations, where the high-magnitude earthquakes will occur in potential, is one of the scientific goals of the studies on long-term faulting behavior of active faults and paleo-earthquakes, and is also the key problem of earthquake prediction and forecast. The study of the geological and seismological signatures for identifying M≥7.0 earthquake risk areas and their application is an important part of seismic prediction researches. It can not only promote the development of earthquake science, especially the progress of earthquake monitoring and forecasting, but also be positive for earthquake disaster prevention and effective mitigation of possible earthquake disaster losses. It is also one of the earthquake science problems which the governments, societies and the scientific communities are very concerned about and need to be addressed.
Large or great earthquakes, such as the 2008 Wenchuan earthquake(M8.0), the 2010 Yushu earthquake(M7.1), the 2013 Lushan earthquake(M7.0)and the 2015 Gorkha earthquake(MW7.8), have unceasingly struck the Qinghai-Tibet Plateau and its surrounding areas, which have been attracting attention of a large number of geoscientists both at home and abroad. Owing to good coverage of the seismic networks and GPS sations, a lot of high-quality publications in seismicity, crustal velocity structure, faulting beihavior have been pressed, which gives us a good chance to summarize some common features of these earthquakes. In this paper, seismogenic structural model of these earthquakes, faulting behavior of seismogenic faults, crustal mechanical property, recent straining environment and pre-earthquake seismicity are first analyzed, and then, five kinds of common features for the sismogenic faults where those earthquakes occurred. Those five kinds of commom features are, in fact, the geological and seismological signatures for identifying M≥7.0 earthquake risk areas. The reliability of the obtained sigatures is also discussed in brief. At last, based on the results of 1:50000 active fault mapping, and published seismic tomography and fault-locking studies, an experimental identification of the risk areas for the future large/great earthquakes in the North China and the Qinghai-Tibet Plateau is conducted to test the scientificity and applicability of these obtained sigantures. 相似文献
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By combining conventional grey correlation analysis,grey clustering method and grey forecasting methods with our multi-goal forecast thoughts and the techniques of grey time series processing,we develop six different grey earthquake forecast models in this paper,Using the record of major earthquakes in Japan from 1872 to 1995,we forecast future earthquakes in Japan.We develop an earthquake forecast model.By using the major earthquakes in Japan from 1872 to 1984,we forecast earthquakes from 1985 to 1995 and check the precision of the grey earthquake models.We find that the grey system theory can be applied to earthquake forecast.We introduce the above analysis methods and give a real example to evaluate and forecast.We also further discuss the problems of how to improve the precision of earthquake forecast and how to strengthen the forecast models in future research. 相似文献
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The definition and abnormality discriminatory criteria of earthquake flow function are introduced in this paper based on the algorithm of Space Increased Probability (SIP). Nine earthquake flow functions were defined by the method. The retrospect test that applied the SIP algorithm with the nonlinear earthquake flow function to 7 earthquakes, which occurred from 1975 to 1989 in Eastern China, with a magnitude of 6 or greater depicted that 6 of the 7 strong earthquakes (86%) were located in the SIP areas, and the SIP covers about 32% of the total research time-space domain. These suggest that the R-value, an effective scale for earthquake forecast, is 54% and may imply that the nonlinear earthquake flow function introduced in this paper can be applied to the intermediate-term earthquake forecast research. 相似文献
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本文基于中国大陆西部流动重力测量获得的区域重力场变化数据, 尝试对其进行多种位场变换, 在一定空间尺度约束下定义了6种区域重力场变化指标量. 在此基础上, 以中国大陆2002年、 2005年和2008年等3期数据为研究对象, 计算并统计了中国大陆西部MS≥6.0地震震中位置处震前重力场变化及各种导出参数值, 尝试初步构建以地震预报为目的的地震重力学科指标体系参数. 研究结果表明, 震前区域重力场变化与地震发生位置没有显著的统计关系, 但是重力场变化的垂直梯度和解析信号模量具有一定的地震预报意义, 适合作为地震前兆异常使用. 相似文献
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Reservoir earthquake characteristics such as small magnitude and large quantity may result in low monitoring efficiency when using traditional methods. However, methods based on deep learning can discriminate the seismic phases of small earthquakes in a reservoir and ensure rapid processing of arrival time picking. The present study establishes a deep learning network model combining a convolutional neural network (CNN) and recurrent neural network (RNN). The neural network training uses the waveforms of 60 000 small earthquakes within a magnitude range of 0.8-1.2 recorded by 73 stations near the Dagangshan Reservoir in Sichuan Province as well as the data of the manually picked P-wave arrival time. The neural network automatically picks the P-wave arrival time, providing a strong constraint for small earthquake positioning. The model is shown to achieve an accuracy rate of 90.7% in picking P waves of microseisms in the reservoir area, with a recall rate reaching 92.6% and an error rate lower than 2%. The results indicate that the relevant network structure has high accuracy for picking the P-wave arrival times of small earthquakes, thus providing new technical measures for subsequent microseismic monitoring in the reservoir area. 相似文献
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地震预报中最难的是临震预报,而且最需要的也是临震预报。因此,寻找一种临震指标是非常重要的。大地微电流异常可能是一种能在地震前出现异常的观测方法,它具有地震前突变异常,而且是异常幅度明显的指标。通过大地微电流在云南,新疆,黑龙江和中国地震局地质研究所7个台站的实际观测结果可见,一般在地震前几天到20天左右出现异常,异常持续时间约2天。我们根据其异常规律,预测过5个地震的发生,特别是2007年6月3日云南省普洱6．4级和2008年7月7日黑龙江龙江县4．6级地震。 相似文献
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基于MaPInfo的中长期地震预测动态系统 总被引：6，自引：1，他引：6
“中长期地震预测动态系统”（MapDEP2000 for Windows)是以强震时－空概率增益综合预测模型与单项地震预测模型的预测效能评价方法为理论基础，以强大的数据为支持，集成桌面地图信息系统（MapInfo0的主要功能而研制完成的运行于Windows9x或以上环境下的地震综合预测系统。系统具有中长期单项预测方法的计算，异常提取，效能评价，概率增益统计，外推预测和概率增益综合预测等计算与各种输入／输出，图形显示等强大而实用的功能，为运用数据库和GIS实现多手段，多尺度，动态和交互的信息综合，进行地震预测提供了一套实用的系统和完整的解决方案，本文对该系统的科学依据，设计思想和主要功能进行了介绍。 相似文献
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地震滑坡的滑距与重力滑坡的滑距有着显著的不同,科学预测地震发生时黄土地区滑坡的滑动距离是合理评估黄土地区滑坡风险和减轻滑坡灾害的有效方式之一。基于海原特大地震诱发黄土滑坡的400组野外调查数据,通过引入BP神经网络算法,论证了BP神经网络模型用于预测黄土地震滑坡滑距的适宜性和可行性;建立了地震诱发黄土滑坡滑距的BP神经网络预测模型,并通过67组数据进行了验证。BP神经网络算法和传统多元线性回归、多元非线性回归结果的对比显示,BP神经网络的预测更接近真实情况,具有较为理想的预测效果,可以用于黄土地震滑坡滑距的预测,并为圈定较为可靠的致灾范围提供依据。 相似文献
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本文把神经网络方法引进地震预报研究当中。使用地震频次，最大震级，平均震级，等价地震次数等多项地震活动性指标作为神经网络的输入，未来时段内的最大地震震级作为其输出，可以对某一固定地区的最大地震震级作出中近期预报。选用的神经网络模型为含两个中间层的前向模型，并采用ＢＰ算法。所得结果表明，用神经网络方法可以在一定精度范围内使震级预报的内检符合率达到１００％，在本文的例子中，外推预报准确率达到６０％以上。 相似文献
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Scaling relations previously derived from examples of the precursory scale increase before major earthquakes show that the precursor is a long-term predictor of the time, magnitude, and location of the major earthquake. These relations are here taken as the basis of a stochastic forecasting model in which every earthquake is regarded as a precursor. The problem of identifying those earthquakes that are actually precursory is thus set aside, at the cost of limiting the strength of the resulting forecast. The contribution of an individual earthquake to the future distribution of hazard in time, magnitude and location is on a scale determined, through the scaling relations, by its magnitude. Provision is made for a contribution to be affected by other earthquakes close in time and location, e.g., an aftershock may be given low weight. Using the New Zealand catalogue, the model has been fitted to the forecasting of shallow earthquakes exceeding magnitude 5.75 over the period 1965–2000. It fits the data much better than a baseline Poisson model with a location distribution based on proximity to the epicenters of past earthquakes. Further, the model has been applied, with unchanged parameters, to the California region over the period 1975–2001. There also, it performs much better than the baseline model fitted to the same region over the period 1951–1974; the likelihood ratio is 1015 in favor of the present model. These results lend credence to the precursory scale increase phenomenon, and show that the scaling relations are pervasive in earthquake catalogues. The forecasting model provides a new baseline model against which future refinements, and other proposed models, can be tested. It may also prove to be useful in practice. Its applicability to other regions has still to be established. 相似文献
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IntroductionThe earthquake sequences can be divided as the type of isolation (single shock), mainaftershocks and swarm of earthquake (multi-shocks) (Institute of Geophysics of CAS, 1976; Li,1981; Wu, et al, 1990). Based on the research of earthquake sequence, combined with modernobservation technique and the wide band strong (main) shock records of CDSN, this paper willdetermine the properties of hypocenter and seek the internal relation between the type of earthquake sequence and the hypo… 相似文献