全球定位系统GPS技术及其在地球动力学方面的应用

本文简述了GPS测量技术 ,重点介绍了福建地壳形变GPS观测网利用GPS定位技术在地壳形变监测方面及其在地球动力学方面的应用 ,并取得了有重要意义的科学成果。     

通渝隧道围岩变形的神经网络预测

隧道新奥法施工中 ,常以围岩变形量作为评判围岩稳定性和支护结构经济合理性的重要指标。公路隧道围岩变形量是随时间而变化的数据序列 ,因而可以建立一些实时跟踪预测模型和方法。根据通渝隧道围岩拱顶下沉位移变形的特性 ,采用神经网络技术来预测其变形量 ,结果表明该方法简易、有效     

美国长期生态研究计划：背景、进展和前景

由美国国家科学基金会支持的长期生态研究计划于1980年启动，至今在理论研究、开发技术和服务社会方面都取得了举世瞩目的成就。该计划的发展分为 3个阶段，每一阶段大约为10年。在其发展的第一个阶段，是以研究站所代表的生态系统为研究对象，主要开展了生态系统的过程与格局方面的研究并系统采集和存贮了有关数据；在1990 -2000年的第二个发展阶段中，其研究工作的重点是开展跨站的网络研究和人类活动对生态系统的影响，以揭示生态系统的过程与格局在较大空间尺度上的特征；按照规划，美国长期生态研究计划的发展进入到第三个阶段后，其工作的重点是开展综合研究、进行生态预测和更好地为社会发展服务，同时加强生物多样性的研究和信息学的发展。     

人工神经网络在岩体质量分级中的应用

结合四川省金沙江某水电站工程实例，应用BP人工神经网络方法建立3层BP网络模型，选取岩石单轴抗压强度等6个影响因素为输入变量，对坝基复杂岩体进行质量分级。通过机算机Visual C 语言编程实现神经网络模型，进行网络的学习和运算。以神经网络合理结构分析方法选取合理结构，确定合理隐层单元的数量，提高网络测试的精度。对测试结果的分析发现，经过优化的BP网络模型经多次学习后，测试精度提高，结果可靠，取得较好的实际应用效果。     

昌马水库右岸山体稳定性研究

昌马水库导流排砂洞塌方导致右岸山体发生松动 ,本文在大量地质资料的基础上 ,对右岸岩体裂隙网络进行模拟 ,同时 ,采用极限分析能量法和有限元数值模拟方法等对右岸山体的稳定性进行分析研究 ,并提出相应的加固方案。     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

London and Frankfurt in Europe's evolving financial centre network

The launch of the Euro and the location of the European Central Bank in Frankfurt initially was seen as a threat to London's pre-eminent position in European financial geographies. This paper explains why in fact this was not the case. To do this, the paper is divided in two. Firstly, it reviews the literatures that help to explain financial geographies. It is argued that we need to move away from investigating attribute properties such as financial turnover and instead examine the role of networks and interdependencies in producing financial geographies. Secondly, it identifies London's dominance and Frankfurt's growth as a complementary centre through quantitative analysis and then explains how European networks and interdependencies produce this, based on insights from interviews with investment bankers and insurance institution workers in the two cities.     

概率神经网络与BP网络模型在遥感图像分类中的对比研究

通过分析概率神经网络(以下称PNN)的基本结构及其训练算法,建立了卫星图像分类的概率神经网络模型,并通过实例对比分析了概率神经网络与BP网络分类模型的分类效果。实验表明,PNN图像分类方法在分类精度上优于误差反向传播神经网络模型,且分类时间相当,是一种有效的图像分类方法。     

陕西省信用联社市县级计算机网络防雷工程设计分析

“山西省卫星农网”依托其省、市、县三级专门服务于农业的信息交流平台,能够及时地让农户了解国家和地方的农业政策及办事程序等,成为农户和政府间的信息桥梁,为广大农村提供准确的各类气象信息,有效地指导了农业生产,大大地减小了天气灾害损失。山西卫星农网作为山西省规模较大的农业专业网站,其影响和作用正逐步地发挥出来。     

Computation of response spectra from mining tremors using neural networks

Underground coal and copper ore exploitation in two Polish mining regions causes mining tremors and a series of other negative phenomena in the environment. Although these tremors are strictly connected with human activity, they differ considerably from other paraseismic vibrations. The moment of their occurrence is not to be foreseen likewise for earthquakes. The main problem discussed in the paper was formulated as the neural network evaluation of a relation between mining tremor energies, epicentral distances and acceleration response spectra. Back-propagation neural networks with Resilient back-propagation learning method were used. Each input vector included information about the mining tremor energy and the epicentral distance. Values of acceleration response spectrum were expected as the outputs of neural networks. Neurally evaluated spectra were compared with spectra computed on the basis of experimental data. After the network is trained and tested, it can be used for mapping of new data of mining tremor energies and epicentral distances into the spectra. Then, what is the substantial advantage of neural approach, the prediction of acceleration response spectra can be performed without recording of surface vibrations. In the light of the results, it is visible that the presented way of computation of acceleration response spectra can be peculiarly applied to prognosis of mining tremors influences on structures.