海面矢量和标量粗糙度的相似分析

应用海面矢量和标量廓线，以及贴海层厚度的相似分析，提出并论证了海面矢量与标量粗糙度近似相等的结论。     

Support capacity estimation of a diversion tunnel in weak rock

This paper presents the results of the support capacity estimation for the diversion tunnel of the Uru dam site in highly weathered tuff and weak zone. Tunneling in weak rock requires some special considerations, since misjudgment in support design results in costly failures. There are several ways of estimating rock support pressure and selecting support. However, all systems suffer from their characteristic limitations in achieving objectives. Thus, it is more useful to use different methods for estimating support pressure and type of support. The support pressure p_i was established by three different methods. These methods are the (1) empirical methods based on rock mass rating (RMR) and rock mass quality index (Q-classification systems), (2) ground support interaction analysis (GSIA) and (3) numerical methods, namely, Phase² finite element (FEM) program. Rock masses were characterized in terms of RSR, RMR, Q-system and GSI. Drill-core samples were tested in the rock mechanics laboratory to determine physico-mechanical properties. Rock mass strength was estimated by empirical methods. Finally, the required support system is proposed and evaluated by different methods in the highly weathered tuff and weak zone of the diversion tunnel.     

GPS三维基线向量向大地坐标差的直接转换

推导了ＧＰＳ三维基线向量向大地坐标差直接转换公式,编制出相应的转换程序。     

栅格数据矢量化及其存在问题的解决

矢量结构和栅格结构是GIS的两种主要数据结构形式，而栅格数据的矢量化在GIS中具有十分重要的意义。本文在总结前人算法的基础上，以拓扑关系的原理为指导，提出了改进的栅格结构数据矢量化方法，即在提取结点和坐标点过程中同时提取水平和垂直的所有线段信息，以便于快速、有效地实现栅格数据的矢量化。此外，还采用动态打断和粗网格法等方法，解决了在栅格数据矢量化过程中经常出现的诸如多边形自交、岛等问题。     

处理非线性分类和回归问题的一种新方法（Ⅰ）——支持向量机方法简介

简要介绍了近年来倍受瞩目的一种处理高度非线性分类、回归等问题的计算机学习的新方法——支持向量机(SVM)方法；分析了这一方法的特点及其在数值预报产品释用及气象研究业务中的应用前景。SVM是一种有坚实理论基础的新颖的小样本学习方法。它基本上不涉及概率测度及大数定律等，因此不同于现有的统计方法。从本质上看，它避开了从归纳到演绎的传统过程，实现了高效的从训练样本到预报样本的“转导推理”(transductive inference)，大大简化了通常的分类和回归等问题。SVM的最终决策函数只由少数的支持向量所确定，计算的复杂性取决于支持向量的数目，而不是样本空间的维数，这在某种意义上避免了“维数灾”。     

Stochastic analysis of immiscible displacement of the fluids with arbitrary viscosities and its dependence on support scale of hydrological data

Stochastic analysis is commonly used to address uncertainty in the modeling of flow and transport in porous media. In the stochastic approach, the properties of porous media are treated as random functions with statistics obtained from field measurements. Several studies indicate that hydrological properties depend on the scale of measurements or support scales, but most stochastic analysis does not address the effects of support scale on stochastic predictions of subsurface processes. In this work we propose a new approach to study the scale dependence of stochastic predictions. We present a stochastic analysis of immiscible fluid–fluid displacement in randomly heterogeneous porous media. While existing solutions are applicable only to systems in which the viscosity of one phase is negligible compare with the viscosity of the other (water–air systems for example), our solutions can be applied to the immiscible displacement of fluids having arbitrarily viscosities such as NAPL–water and water–oil. Treating intrinsic permeability as a random field with statistics dependant on the permeability support scale (scale of measurements) we obtained, for one-dimensional systems, analytical solutions for the first moments characterizing unbiased predictions (estimates) of system variables, such as the pressure and fluid–fluid interface position, and we also obtained second moments, which characterize the uncertainties associated with such predictions. Next we obtained empirically scale dependent exponential correlation function of the intrinsic permeability that allowed us to study solutions of stochastic equations as a function of the support scale. We found that the first and second moments converge to asymptotic values as the support scale decreases. In our examples, the statistical moments reached asymptotic values for support scale that were approximately 1/10000 of the flow domain size. We show that analytical moment solutions compare well with the results of Monte Carlo simulations for moderately heterogeneous porous media, and that they can be used to study the effects of heterogeneity on the dynamics and stability of immiscible flow.     

土质边坡支护工程中几种特殊情况的处理

因工程建设需要，常使某些复杂地层形成边坡。松散人工填土、砂卵石层、流砂层、淤泥层等和水害，是土质边坡支护的重点，处理不当，将导致边坡坍塌，酿成灾害性后果。土钉、锚杆是土质边坡支护工程中的有效方法，支护过程中先施工注浆土钉、后施工注浆锚杆；借用千斤顶压入钢管土钉、二次注浆等工艺措施，达到快速稳定边坡之目的。治理水害，应先查清水源，再根据具体情况分别采取堵、排、挡、滤、抽等方法，以达到永久性边坡治水的目的。支护工程中，应把握好设计、监测等环节，遇到特殊情况及时处理，避免灾难性事故发生。     

1983—1992年中国陆地植被NDVI演变特征的变化矢量分析

以NDVI时序资料为基本数据源，综合应用变化矢量分析和主成分分析方法对1983年至1992年中国陆地植被NDVI的变化强度、变化类型及空间结构变化特征进行了分析。研究结果表明在此期间中国陆地植被NDVI变化有以下特点：（1）十年间NDVI变化东西分异明显，东部变化幅度远大于西部。NDVI变化整体表现为稳中略增，增加区主要分布在台湾、福建、四川、河南等地；减少区主要分布在云南省和新疆北部等地。（2）空间结构信息表现了景观异质性，其变化主要发生在南方，反映了植被的生长和衰老过程及地形（山脉走向）变化。     

支撑向量机及其遥感影像空间特征提取和分类的应用研究

提出了基于支撑向量机（SVM）的遥感影像空间特征提取的新方法，并以SPOT全色波段影像上城市特征信息的提取为应用实例，并与人工神经网络（ANN）等特征提取方法进行综合比较，认为SVM方法不但能够获得比较高的分类精度，而且在学习速度、自适应能力、特征空间高维不限制、可表达性等方面具有优势。     

SVG网络图像标准支持下的地图显示

介绍了一种全新的网络图像标准SVG（Scalable Vector Grcphics），分析了目前网上地图显示的方法，探讨了运用SVG在网上进行地图显示的可能性，提出了其应用体系和结构。