岫岩5.4级地震前后拐角频率比的变化特征

本文在利用多台研究1999年11月29日和2000年1月12日发生在辽宁岫岩Ms5.4级和5.1级地震前拐角频率比随时间变化的基础上,对岫岩、营口、苏家屯、丹东、宽甸、北镇、新民单台记录的纵横波拐角频率比fcp/fcs做了比较详细的波谱分析。结果表明:在震中距小于200 km以内的不同方向的台站,记录到的地震波拐角频率比值在5.4级前和后均出现不同程度的异常显示,能够捕捉到一些带有短临性质的信息,不过,距震中较远的台站,地震波拐角频率比值在震前异常不如近台明显,表明不同距离的台站,记录的地震拐角频率比值存在着差异。     

Integration of transfer function model and back propagation neural network for forecasting storm sewer flow in Taipei metropolis

Typhoons and storms have often brought heavy rainfalls and induced floods that have frequently caused severe damage and loss of life in Taiwan. Our ability to predict sewer discharge and forecast floods in advance during storm seasons plays an important role in flood warning and flood hazard mitigation. In this paper, we develop an integrated model (TFMBPN) for forecasting sewer discharge that combines two traditional models: a transfer function model and a back propagation neural network. We evaluated the integrated model and the two traditional models by applying them to a sewer system of Taipei metropolis during three past typhoon events (NARI, SINLAKU, and NAKR). The performances of the models were evaluated by using predictions of a total of 6 h of sewer flow stages, and six different evaluation indices of the predictions. Finally, an overall performance index was determined to assess the overall performance of each model. Based on these evaluation indices, our analysis shows that TFMBNP yields accurate results that surpass the two traditional models. Thus, TFMBNP appears to be a promising tool for flood forecasting for the Taipei metropolis sewer system. For publication in Stochastic Environmental Research and Risk Analysis.     

长波辐射(OLR)信息预测华北地震的方法研究

利用卫星对地遥测长波辐射(OLR)信息,分析了华北地块OLR信息场的空间分布及其变化特征,结合地震活动分布特点进行了短期预测中强地震判定指标的方法研究。结果表明该方法可对华北地区短期内有无可能发生M5以上的显著地震做出较为明确的诊断。经近一年的实际检验效果良好,对华北地区震情监测预报有实用价值。     

利用多元地震属性预测测井特性

通过寻找井旁地震数据与测井曲线的关系,将这一关系应用到远离井的区域(只有地质数据,但无测井)来预测测井的有关特性,其方法有单属性分析和多属性分析[1]。本文通过实例描述了多属性分析的特点及预测结果。从单属性回归到多属性预测、再到神经网络预测过渡时,预测能力持续提高。同时对地震属性的选择和有效性进行了讨论,将结果应用到整个二维地震剖面上,能更好地确定井以外区域的测井特性。     

辽宁地震信息网络通讯线路的设计与实施

从辽宁省地震局信息网络建设的实际需求出发,采用层次化设计方法,将通讯线路分为三层:即区域中心、汇聚层和台站。各层之间采用2MSDH传输电路实现层间连接,通过路由器的配置来保证数据流的畅通,实现了全网互联互通。本文介绍了辽宁地震信息网络通讯线路的设计与实施过程。     

利用卫星云图定量分析副热带高压活动的方法及应用

利用数字图像处理方法，设计了一种多重处理的算法，从卫星云图提取定量信息，定量描述副高强度和演变趋势，并应用于预报业务。应用实践表明，这些方法具有客观、定量、自动等优点，在实际使用中可客观定量地跟踪和预报副高演变，对做好广西前汛期暴雨预报有较大的帮助。     

多种降阻材料搭配在变电站接地网改造中应用

在北海市三塘110KV变电站接地网系统改造工程实践中，通过不等长接地体技术及多种将阻材料搭配使用，克服了原接地网接地电阻值增大因素，并对变电站接地网改造和施工工艺进行设计。     

Location Accuracy of the China National Seismograph Network Estimated by Repeating Events

INTRODUCTIONDigital seismological observation in China has had a significant development in recent years,especiallysince the last five years(Liu Ruifeng,et al.,2003).For further development,it isnecessarytoassessthe monitoringcapabilityof the existingseismological network.One of theimportantassessments is the estimation of regionalizedlocation accuracy.Upto present,several approaches have been proposed to assess the location accuracy,such asthe groundtruth event approach(e.g.,Lienert,199…     

磁异常数据处理方法的应用

文章以冀东一些铁矿区地面磁测成果为例,总结了磁异常转换、定量解释推断一些方法的应用及效果.     

DOWNSCALING FORECAST OF MONTHLY PRECIPITATION OVER GUANGXI BASED ON BP NEURAL NETWORK MODEL

Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast.