Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

Most likely locations of large earthquakes in the Kanto and Tokai areas, Japan, based on the local recurrence times

We examined the hypothesis that minima in local recurrence time, T_L, or equivalently maxima in local probability, P_L, may map asperities in the Kanto and Tokai areas of Japan, where the earthquake catalog of the National Research Institute for Earth Science and Disaster Prevention (NIED) is complete at the M=1.5 (M1.5) level. We mapped T_L (P_L) based on the a- and b-values of the nearest earthquakes within 20 km of every node of a grid spaced 0.01° for M7 target events. Only earthquakes within the top 33 km were used. The b-values increase strongly with depth, in several areas. Therefore, some of the T_L (P_L) anomalies are not revealed if data from the entire crustal seismogenic zone are mixed. Thus, we mapped T_L (P_L) separately for the top 15 km and the rest of the depth range, as well as for the entire seismogenic crust. The resulting T_L- and P_L-maps show that approximately 12% of the total area shows anomalously short recurrence times. Out of six shallow target events with M≥6.5 and which occurred since 1890, five are located within the anomalous areas with T_L <450 years. We interpret this to mean that areas with anomalously short T_L map asperities, which are more likely than other areas to generate future target events. The probability that this result is due to chance is vanishingly small. The great Kanto rupture of 1923 appears to have initiated in the most significant asperity we mapped in the study area. One anomaly is located in the northeastern part of the area of the proposed future rupture of the Tokai earthquake, and another one at its southwestern corner. The absolute values of T_L calculated are uncertain because they depend on the size of the volume used for the calculation.     

浅谈地震保险的必要性及其作用

以防震减灾为视角，针对地震灾害对社会发展及人民生活造成的重大损失，从强化地震保险意识的角度，论述地震保险的必要性和重大意义。同时对地震保险在心理、补偿、救灾、缓冲、防灾及附带等方面的作用加以阐述，从而证明要减少地震灾害的损失，充分认识地震保险的必要性及其作用，建立和完善有效的保险机制，对于减轻地震灾害，促进社会发展和人民安居乐业是一项必要的基础性工作。     

城市震害高危害小区的研究和GIS的实现技术

论述了在城市地震灾害中如何考虑诸方面因素来评价城市的灾害轻重分布情况。中建立坑危害小区分析模型，设想将城市划分等面积网格，给每个单元网格赋予灾害指数，以确定城市中受灾较为严重的区域，为求灾指挥提供决策信息。同时，将高危害小区的模型研究结果转化为计算机技术可以实现的GIS模型。该研究结果已应用于泰安市防震减灾示范研究项目中。     

1999年台湾7.6级大震与江苏-南黄海地区中强震预测

分析讨论了台湾地区7级大震与本区中强震之间相关关系，指出1999年台湾7.6级大震后2－3年内，本区将有5－6级中强震发生。同时应用可公度模型和“带头地震”的异年倍九法联合对本区中强震发震时间进行分析预测。结论表明，该方法可以较好地应用于本区短临地震预报实践。     

云南中强震的水氡前兆异常特征

2001年云南澜沧5.0、施甸5.2,5.9,5.3、宁蒗5.8、楚雄5.3和江川5.1级地震前，云南49项水氡前兆中的一些台站出现突出的异常。研究发现，根据这些异常项的异常特征和空间分布特征及历史震例，可对这几次地震预报的三要素，尤其是地点和时间做出较好的判断。     

川滇地区地震(Ms≥5.0)破裂类型与前兆异常分布的关系

对川滇地区 31次 (组 ) 5 .0级以上地震与余震次数的关系进行了统计 ,结合“强地震分为走滑型地震和断错型地震”的理论 ,确定了各次 (组 )地震的破裂类型。从物理机制上对地震破裂类型与震前前兆异常分布关系进行了讨论 ,由此进一步探讨了 5 .0级以上地震震后趋势预测     

基于Exchange Server 5.0前兆网络邮件系统的建立

各省地震局 95 - 0 1- 0 2地震信息网络项目采用的邮件系统是基于 IRIX 6 .5操作系统的Netscape Mail Server2 .0 ,由于其应用与管理有局限性 ,笔者进行了基于 NT系统的 ExchangeServer5 .0邮件系统的应用研究 ,详细论述了基于 Exchange Server5 .0的黑龙江省地震前兆信息网络邮件系统的安装及配置过程 ,得出该网络邮件系统有管理方便、功能强大的结论     

河南豫北地震台网地区波速的探讨

为了解决河南豫北地区地震的定位问题 ,对豫北台网内的 10个典型地震 ,使用了 7个地震台站的资料 ,用波速比求出横波速度 ;用和达定位法 (有的同时使用高桥法 )进行了精确定位 ,求出震源深度 ;测量了震中至各台的震中距 ,以此反算出了纵波速度。通过计算 ,确定出了较为适合河南豫北地震台网地区的波速。     

A study on the early-warning technique concerning debris flow disasters

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN)real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system′s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.