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。     

基于三角网渐进式简化的等高线多尺度综合

提出了一种基于三角网渐进式简化的等高线多尺度综合方法,实验结果表明,其不仅可以较好地保留地形特征,而且可以完全避免等高线相交现象的产生.     

GPS高程转换的神经元网络方法分析

GPS高程转换是GPS高程应用的关键问题之一，试图应用神经元网络方法来进行GPS高程的转换，并在网络的拓扑结构与网络结构的改进等方面作了分析，通过GPS高程转换的二次曲面法和神经元网络法进行了比较试验，结果表明了神经元网络转换GPS高程的可行性和可靠性，对于应用神经网络转换GPS高程具有实际的指导意义。     

Black Holes and Loose Connections in a Global Urban Network

This paper introduces the concept of black holes and loose connections in a global urban hierarchy. Black holes are defined as large cities, with a population of over 3 million, that are not classified as world cities. The paper draws upon a classification that uses advanced producer services as an indicator of world city status. Large, nonworld cities are identified, and provisional ideas about explaining their position are outlined. Connectivity and population data are used in a simple regression analysis to identify loose connections: cities whose connectivity is less than that predicted by their population.     

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.     

储层岩石电性特征的逾渗网络模型研究(英文)

建立能够反映储层孔隙结构、流体特征的逾 渗网络模型,通过数值模拟研究了储层孔隙尺寸、 孔隙形状、连通性、微孔隙的发育状况等对I-Sw曲 线影响的定性规律,研究了地层水矿化度对岩石电 阻率的影响。分析讨论了不同因素对电阻率影响的 相对强度。最后,通过曲线拟合定量地研究了不同 因素对I-Sw曲线的影响规律。研究表明,在上述影 响因素中连通性和微孔隙对I-Sw曲线的影响很大, 其它因素的影响强度较小。地层水矿化度对岩石电 阻率绝对值的影响很大。“非阿尔奇”现象普遍存在, 在低渗透(低连通性)储层岩石中更为明显。