基于神经网络的平底结构砰击压力预报

对利用神经网络预报平底结构入水砰击压力的方法进行了探讨。首先利用仿真软件计算各种情况下平底结构入水所产生的砰击压力，以此形成训练神经网络的数据集。其次利用数据集对三层反馈式网络进行了训练，讨论了不同隐含层节点数对该非线性系统的拟合能力，并且对梯度下降法、动量修正法和基于优化的LM算法的有效性和精度进行了比较，最后得出了适合平底结构入水砰击系统的网络结构。     

渤海、黄海强温跃层数值预报模式

文中对前人关于水温垂直结构计算、模拟和预报研究成果进行了评价，并在此基础上建立了考虑海面吸收辐射和透射辐射、地形、风、海流、界面摩擦及其引起的混合作用的强温跃层三维数值预报模式。该模式运行的驱动量仅为风和气温场资料，因而具有较好的实用性；此外，从试报的结果看，效果是令人满意的。     

能量分析在台风短期预报业务中的应用

本文以９４１４、９４１５号两个连续北上台风为例，证明能量场的分布与台风移向有着明显的对应关系。     

GIS在处置地下管线突发事件中的应用研究——以苏州市地下综合管网应急处置系统为例

随着经济社会的不断发展,城市建设步伐不断加快。近几年,各类地下管线突发事件频发。通过"苏州市地下综合管网应急处置系统"项目的开发和实践,本文试图从总体上论述地下综合管网突发事件的处置过程、应用原理及相关的技术实现,重点阐述了基于"12345"便民服务中心工作平台,在充分利用GIS的网络分析技术的基础上,实现城市地下管网突发事件应急处置的自动化和信息化。     

地震综合效应场函数及其在地震预报中的应用──（一）地震综合效应场函数及其计算方法

在系统地分析了目前各种测震学地震预报方法科学思路的基础上,认为测震学地震预报方法基本上可以分为两大类。一类是以已经发生的一些地震作为未来可能发生的地震的“因”,即由于已经发生的地震对区域应力场的影响,导致未来发生较强地震。这一类包括的预报方法较多,如空区、条带、ｂ值、地震迁移、相关地震等等及其由此衍生出来的各种方法。另一类是把已经发生的一些地震作为区域应力场增强的“果”,即已经发生的地震是区域应力场增强过程中的一种反映,而未来地震不一定是已经发生的地震所导致的结果。这一类包括“地震窗口”、小震群活动等方法。针对第一类方法,各种预报方法都是力图从地震三要素中提取未来地震的信息,而具体作法又都是利用地震三要素这个多维空间的某个剖面。为了从地震活动诸要素的多维空间提取综合信息,我们对每个地震加入了破裂面方位,构成了地震第四要素,并依据地震４要素建立了地震综合效应场函数。地震综合效应场函数概括了多种测震学地震预报方法的科学思路和预报经验,从而可以形成测震学的综合预报方法。     

Prediction of the occurrence of Related Strong Earthquakes in Italy

In the seismic flow it is often observed that a Strong Earthquake (SE), is followed by Related Strong Earthquakes (RSEs), which occur near the epicenter of the SE with origin time rather close to the origin time of the SE. The algorithm for the prediction of the occurrence of a RSE has been developed and applied for the first time to the seismicity data of the California-Nevada region and has been successfully tested in several regions of the world, the statistical significance of the result being 97%. To date it has been possible to make five successful forward predictions, with no false alarms or failures to predict.The algorithm is applied here to the Italian territory, where the occurrence of RSEs is a particularly rare phenomenon. Our results show that the standard algorithm is successfully directly applicable without adjustment of the parameters. Eleven SEs are considered. Of them, three are followed by a RSE, as predicted by the algorithm, eight SEs are not followed by a RSE, and the algorithm predicts this behaviour for seven of them, giving rise to only one false alarm. Since, in Italy, often the series of strong earthquakes is relatively short, the algorithm has been extended to handle such a situation. The result of this experiment indicates that it is possible to attempt to test a SE, for the occurrence of a RSE, soon after the occurrence of the SE itself, performing timely preliminary recognition on reduced data sets. This fact, the high confidence level of the retrospective analysis, and the first successful forward predictions, made in different parts of the World, indicates that, even if additional tests are desirable, the algorithm can already be considered for routine application to Civil Defence.     

“煤特征指数”与矿井瓦斯危险类型的关系

矿井瓦斯危险程度与煤层中瓦斯赋存状况及其泄出方式有关,并取决于多种地质条件和采掘工艺。其中,煤特征条件特别重要。本文分析了湖南省的5种矿井瓦斯危险类型以及相应的煤特征条件,提出了“煤特征指数(I_c)”这一概念。I_c是一项评价矿井瓦斯危险程度的综合指标。研究表明,矿井瓦斯危险愈严重,则其I_c值愈高。应用该项成果预测了16对矿井的瓦斯危险类型,取得了满意的效果。     

Comparison of structural and least-squares lines for estimating geologic relations

Two different goals in fitting straight lines to data are to estimate a true linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating true straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal—predicting the dependent variable—OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples.     

Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8»

Analyzing the tables and probability maps posted by Yan Y. Kagan and David D. Jackson in April 2002–September 2004 at http://scec.ess.ucla.edu/~ykagan/predictions_index.html and the catalog of earthquakes for the same period, the conclusion is drawn that the underlying method could be used for prediction of aftershocks, while it does not outscore random guessing when main shocks are considered.     

A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models.The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data.