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。     

我国国家大地网的地壳形变改正探讨

以2000网为例，根据1991～2001年累积的GPS重复观测资料，利用GIPSY软件建立具有1115个测点的地壳运动模型。在此基础上，采用双三次样条函数数值拟合法，模拟出2000网网点相对西安基准站的地壳形变改正值，并给出了效果图。     

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。     

Analysis of village accessibility and its impact on land use dynamics in a mountainous province of northern Vietnam

Surveys carried out in mountainous areas of northern Vietnam at research sites selected across a gradient of market integration, revealed strong relationships between the location of the village with respect to the national road network and the nature of its land-use systems, its poverty level and more generally its potential for development. We developed and tested in Bac Kan province a method to give an objective and quantitative definition of accessibility over a large geographic area. Accessibility maps integrated in a provincial GIS showed that despite recent improvements to the road network, some remote areas do not benefit from recent development.     

Sediment concentration changes in runoff pathways from a forest road network and the resultant spatial pattern of catchment connectivity

Hydrological connectivity is a term often used to describe the internal linkages between runoff and sediment generation in upper parts of catchments and the receiving waters. In this paper, we identify two types of connectivity: direct connectivity via new channels or gullies, and diffuse connectivity as surface runoff reaches the stream network via overland flow pathways. Using a forest road network as an example of a landscape element with a high runoff source strength, we demonstrate the spatial distribution of these two types of linkages in a 57 km² catchment in southeastern Australia. Field surveys and empirical modelling indicate that direct connectivity occurs primarily due to gully development at road culverts, where the average sediment transport distance is 89 m below the road outlet. The majority of road outlets were characterised by dispersive flow pathways where the maximum potential sediment transport distance is measured as the available hillslope length below the road outlet. This length has a mean value of 120 m for this catchment. Reductions in sediment concentration in runoff plumes from both pathways are modelled using an exponential decay function and data derived from large rainfall simulator experiments in the catchment. The concept of the volume to breakthrough is used to model the potential delivery of runoff from dispersive pathways. Of the surveyed road drains (n=218), only 11 are predicted to deliver runoff to a stream and the greatest contributor of runoff occurs at a stream crossing where a road segment discharges directly into the stream. The methodology described here can be used to assess the spatial distribution and likely impact of dispersive and gullied pathways on in-stream water quality.