Linux 防火墙的研究与设计

阐述了Linux2．4内核的防火墙Linux的原理，并分析了netfilter的设计与实现，叙述了Linux的动态地址转换，介绍了在Linux下基于netfilter架构如何开发自己的防火墙并给出具体实例。     

The spatial implications of the functional proximity deriving from air passenger flows between European metropolitan urban regions

Until recently the traditional spatial configuration of the European geography was based upon the core-periphery model. The ‘pentagon’, broadly defined as lying between London, Paris, Milan, Munich and Hamburg, was seen as the core area characterised by having the highest concentration of economic development in the European Union (EU), with the remainder of the European territory viewed as peripheral, albeit to varying degrees. In a number of cases such peripheral areas equated with clear regional disparities. The elaboration of the European Spatial Development Perspective (ESDP) (CEC, European spatial development perspective, towards balanced and sustainable development in the territory of the European Union, 1999) challenged this core-periphery model. European spatial planning policies, aimed at encouraging social and economic, and with ever increasing importance, territorial cohesion, seek amongst other aspects to encourage the development of a balanced and polycentric urban system. This paper adopts a network analysis approach to the analysis of air passenger flows between some 28 principal European metropolitan urban regions. The evaluation of these flows contributes to an enhanced comprehension of the spatial dynamics of the European metropolitan territory which goes beyond that deriving from the more standard analyses of the individual components of the urban system. Several indicators are used, deriving from gravitational modelling techniques, to analyse the complexity of the air passenger flows. A multidimensional scaling (MDS) technique is introduced in order to interpret and visualise the resulting spatial configuration and positioning of the different metropolitan centres within the conceptual European ‘space of air passenger flows’, thereby contrasting with the more traditional map-based geographical image of Europe, based upon Cartesian coordinates.

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

用Matlab中的Neural Network Toolbox仿真赤道东太平洋SST的预报模型

基于ＮＣＥＰ／ＮＣＡＲ再分析资料和ＣＯＡＤＳ海洋资料中的全球月平均海平面气压场、８５０hPa纬向风场及海洋温度场，利用Ｍatlab中的Ｎeural Network Toolbox仿真环境和ＢＰ模型改进算法比较准确地仿真和反演出了南方涛动指数、赤道纬向风指数和滞后的赤道东太平洋海温之间的动力结构和预报模型。该模型具有很好的拟合精度和可行的预报效果。可在一定时效内预测赤道东太平洋月平均海温的变化趋势。由于所建系统是具有直接因果关系的预报模型，因此不仅可直接用于预测，而且可有效避免类拟非线性微分方程组在积分过程中由于对初值敏感性而可能产生的对预报结果的不确定性。     

复杂网络河的数值模拟

依据复杂网络河的特点及其内在联系，本文建立了其特征矩阵及由Newton-Raphson格式表述的隐式圣－维南差分方程组的系数矩阵，经输入边界条件及解方程组，可得到不同各支段上，下游端点上的水位和流量值。     

关于城市交通地理信息系统模型设计的思考与改进

GIS—T模型是建立城市交通地理信息系统的主体,本文对现有GIS—T模型进行了简单的分析与评价,并且为了增加政府与公众做出决策的正确性,提出了路径畅通可靠度模型、城市交通综合指数模型、交通出行指数模型三个数学模型,以达到量化城市交通与完善GIS—T模型的目的。     

GPS网络RTK的质量控制

随着科技的发展与工程应用的深入,传统RTK技术的不足也逐渐体现出来。网络RTK的出现克服了它的局限性。本文简要介绍了网络RTK的概念、工作原理、误差来源与平差、质量控制方法。     

The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS

A new method for modeling the ionospheric delay using global positioning system (GPS) data is proposed, called the ionospheric eclipse factor method (IEFM). It is based on establishing a concept referred to as the ionospheric eclipse factor (IEF) λ of the ionospheric pierce point (IPP) and the IEF’s influence factor (IFF) . The IEF can be used to make a relatively precise distinction between ionospheric daytime and nighttime, whereas the IFF is advantageous for describing the IEF’s variations with day, month, season and year, associated with seasonal variations of total electron content (TEC) of the ionosphere. By combining λ and with the local time t of IPP, the IEFM has the ability to precisely distinguish between ionospheric daytime and nighttime, as well as efficiently combine them during different seasons or months over a year at the IPP. The IEFM-based ionospheric delay estimates are validated by combining an absolute positioning mode with several ionospheric delay correction models or algorithms, using GPS data at an international Global Navigation Satellite System (GNSS) service (IGS) station (WTZR). Our results indicate that the IEFM may further improve ionospheric delay modeling using GPS data.     

网络导航中基于SVG的地理空间数据组织与传输

介绍网络导航服务系统,通过对MapX Mobile、ArcPad和SVG的地理空间数据组织的比较,得出基于Mobile SVG的地理空间数据组织方式优于其它两种组织方式。它不但适合网络导航服务系统的数据交互操作,而且同一图幅的数据量也明显少于MapX Mobile、ArcPad两种格式的数据。然后利用gzip软件包对数据进行压缩,减少数据传输所需的时间。     

基于退火BP神经网络的GPS高程转换

阐述模拟退火算法的基本思想和原理,提出并介绍模拟退火算法优化的BP神经网络模型在GPS高程转换中的具体应用,同时编写相应的MATLAB处理程序,结合大量数据进行仿真实验,结果表明文中提出的退火BP神经网络模型具有收敛速度快、精度高、避免陷入局部最小的优良特性。