应用Kriging方法研究格尔木河流域地下水位动态观测网的优化配置

地下水动态是水文地质研究的一个重要方面，如何获满足一定精度要求全面而合理的地下水位动态资料具有现实经济效益。本文研究格尔木河流域地下水位动态测网，通过选取理想的变差函，运有Ｋｒｉｇｉｎｇ方法进行地下水位的线性无偏最优估计和计算估计误差的标准差，结合给定的允许误差限评判地下水位动态观测网的配置是否合适，并提出调整现有观测网的方案     

ADVANCES IN MEASURING TECHNIQUES OF BED LOAD

I.m~UCrIONBedloadisthesedimentwhichmovesalongtheriverbedintheformofrolling,slidingandsaltation.BedloadmaycreatemanyproblemsintheoperationandmaintenanceofnavigationchannelandinthedevelOPmentofhydroelectricity.Dataofbedloaddischargearealsorequiredinthedesignofreservoir,inwhichtheinflowbedloadareallactuallytrapped.Thewaysofbedloadmotionaredifferentfordifferentsizes.Thus,itisextremelydifficulttodeterminethebedloaddischargeaccurately.Manyequationshavebeenproposedtocalculatethebedloaddischarge.H…     

数据采集中特征点粗差定位方法的探讨

本文分析了特征点应满足的几种条件，给出了一次范围最小（Ｌ１）法，最小二乘法以及粗差探测法进行特征点粗差定位方法，并以模拟实例为例对它们进行了比较，得出了一些有意义的结论。     

物理实验中的不确定度评定

阐述了不确定度的定义、来源、分类及用不确定度评定测量结果的一些表示方法。分析了误差和不确定度的区别。最终给出了测量不确定度的评定。     

区域地球化学数据的归一化处理及应用

介绍了一种简单的勘查地球化学数据调整方法———归一化,该方法采用各批或各区块差异数据的平均值或中位数的衬值乘以参照值以获得元素的视含量,用于调整不同分析批次之间的系统误差,或不同背景区数据的差异;用2个实例详细介绍了该方法的应用效果。     

GPS广播星历参数拟合算法

介绍了GPS广播星历参数的最小二乘估计方法。推导了相应的计算公式。计算结果表明。文中给出的公式是正确的，其拟合精度以用户距离误差(URE)示时，对预报轨道的损失小于1cm。     

基于典型相关分析的变化检测中变化阈值的确定

以东营市为例 ,把基于典型相关分析的方法运用于多时相遥感影像的变化检测中。对于变化阈值的确定 ,采用了一种基于贝叶斯理论的最小错误率的方法。这种方法实质上是一种非监督分类的方法 ,即不需要地面实况数据或其它先验知识 ,直接对典型相关处理后的差值图像进行分析计算得到阈值 ,使变化检测的错误率达到最小。实验结果证明了这种方法的有效性。     

基于二维直接线性变换的数字相机畸变模型的建立

提出并论证了基于二维直接线性变换的畸变的校正方法。本方法特别适用于各类固态摄像机(CCD、CID、PSD)的畸变模型的建立，以补偿各类像点系统误差。     

Probabilistic approach for active control of structures: experimental verification

In our previous study (Earthquake Engineering and Structural Dynamics 2003; 32 :2301), we have developed a probabilistic algorithm for active control of structures. In the probabilistic control algorithm, the control force is determined by the probability that the structural energy exceeds a specified target critical energy, and the direction of a control force is determined by the Lyapunov controller design method. In this paper, an experimental verification of the proposed probabilistic control algorithm is presented. A three‐story test structure equipped with an active mass driver (AMD) has been used. The effectiveness of the control algorithm has been examined by exciting the test structure using a sinusoidal signal, a scaled El Centro earthquake and a broadband Gaussian white noise; and, especially, experiments on control have been performed under different conditions to that of system identification in order to prove the stability and robustness of the proposed control algorithm. The experimental results indicate that the probabilistic control algorithm can achieve a significant response reduction under various types of ground excitations even when the modeling error exists. Copyright © 2004 John Wiley & Sons, Ltd.     

Analytical exploration of γ-function explicit method for pseudodynamic testing of nonlinear systems

It has been well studied that the γ-function explicit method can be effective in providing favorable numerical dissipation for linear elastic systems. However, its performance for nonlinear systems is unclear due to a lack of analytical evaluation techniques. Thus, a novel technique is proposed herein to evaluate its efficiency for application to nonlinear systems by introducing two parameters to describe the stiffness change. As a result, the numerical properties and error propagation characteristics of the γ-function explicit method for the pseudodynamic testing of a nonlinear system are analytically assessed. It is found that the upper stability limit decreases as the step degree of nonlinearity increases; and it increases as the current degree of nonlinearity increases. It is also shown that this integration method provides favorable numerical dissipation not only for linear elastic systems but also for nonlinear systems. Furthermore, error propagation analysis reveals that the numerical dissipation can effectively suppress the severe error propagation of high frequency modes while the low frequency responses are almost unaffected for both linear elastic and nonlinear systems.