铜陵地区的镶嵌构造及其控矿意义

铜陵地区是我国著名的铁铜矿区。海西—印支期,环太平洋波浪引起了北东向展布的褶皱群,其背斜是波峰带,向斜是波谷带。印支期,古地中海地壳波浪使本区形成了北西向断裂。北东向构造和北西向构造的交织,形成了区内镶嵌构造格局。北西向断裂控制着铜铁矿床的分布,铅锌矿床则沿北东向的背斜翼部分布,构造的等间距性决定着矿田分布的等间距性。     

A modification of minimum norm quadratic estimation of a generalized covariance function for use with large data sets

Marshall and Mardia (1985) and Kitanidis (1985) have suggested using minimum norm quadratic estimation as a method to estimate parameters of a generalized covariance function. Unfortunately, this method is difficult to use with large data sets as it requires inversion of an n × n matrix, where n is number of observations. These authors suggest replacing the matrix to be inverted by the identity matrix, which eliminates the computational burden, although with a considerable loss of efficiency. As an alternative, the data set can be broken into subsets, and minimum norm quadratic estimates of parameters of the generalized covariance function can be obtained within each subset. These local estimates can be averaged to obtain global estimates. This procedure also avoids large matrix inversions, but with less loss in efficiency.     

防雷工程中的等电位连接问题

本文根据近几年来防雷专家对等电位连接问题的研究成果,结合多年从事防雷工作的实践,对等电位连接问题作了深入的探讨,并就防雷工程中各个环节的等电位连接从设计和施工两个侧面提出了一些看法和建议。     

Misspecification of extreme rainfall population statistics and frequency inference due to measurement bias and variability

Statistical analysis of rainfall extremes is mostly based on the assumption of error-free data, despite common knowledge about the widespread incidence of precipitation measurement bias and variability. The objective of this study is primarily to investigate the impact of measurement bias and variability in statistical classification and quantile estimates of rainfall extremes. A theoretical framework is presented for the analysis of moment coefficients and probability distributions for rainfall extremes corrupted by measurement bias and variability. Furthermore, methods are outlined for practical statistical analysis of error-corrupted rainfall extremes, based on maximum likelihood. Frequency inference and testing for the presence of measurement variability are the main topics. Modelling of data series is undertaken in order to exemplify the statistical assessment and the real-life impact of measurement error.It is shown that: (a) unaccounted measurement error may potentially cause a considerable degree of misspecification about the conventional moment and L-moment coefficients of variation, and the conventional moments of skewness and kurtosis; (b) the presence of measurement variability alone can cause significant and nonlinear quantile bias which further strongly increases with the additional presence of measurement bias; and (c) maximum likelihood estimation provides a general and efficient tool for assessing measurement error in extreme rainfall frequency analysis.     

"莫拉克"台风引起的滑坡泥石流灾害HJ-1图像遥感监测研究

利用HJ-1星2009年"莫拉克"台风前后获取的2个时相图像,通过去相关拉伸 (Decorrelation Stretch)、光谱信息增强和最大似然法分类提取滑坡、泥石流区域,并结合TRMM (Tropical Rainfall Measuring Mission)卫星降雨量数据和DEM (Digital Elevat...     

基于拉剪强度同等折减法的滑坡稳定性分析

以攀枝花教师街滑坡为背景,考虑土体抗拉强度的影响,结合抗剪强度,采用“拉剪强度同等折减法”来研究滑坡的稳定性。通过室内试验,分析了含水率对教师街滑坡不同岩土层的影响规律,发现滑带层土体的内摩擦角和粘聚力受水的作用更加显著。通过利用有限差分软件FLAC和拉剪同等折减法,得到了教师街滑坡的拉剪临界折减系数、临界内摩擦角、临界粘聚力;同时,还发现教师街滑坡对土体的内摩擦角敏感度最高,但是抗拉强度的影响和粘聚力很接近,不容忽视;滑坡坡肩位移大于坡脚位移,应注意坡肩位移的变化。     

水库防洪等蓄量优化调度模型及应用

等蓄量法是中国水库防洪规划与实时调度中常用的调度方式,其3个参数（等蓄流量、起蓄流量和等蓄历时）一直采用试算方法推求。以等蓄流量为输入参数,引入蓄放水0~1状态变量,定义了逐时段水库蓄水量之和最小的线性目标函数,并设置蓄水状态连续性约束解决等蓄历时的推求,建立了水库防洪等蓄量优化调度的0~1整数线性规划模型（RFEV-ILP）。通过亭子口水库应用表明,该模型算法稳定,与理想补偿调度方式计算的防洪库容相差不足1%。该优化模型不仅可以推求防洪库容、起蓄流量及等蓄历时与等蓄流量之间的数值关系,而且能较好地揭示防洪风险与等蓄流量之间的关系、防洪控制点距离水库的远近对等蓄流量可选范围及相应采取防洪策略的影响。     

Estimation of ultimate bond strength for soil nails in clayey soils using maximum likelihood method

This paper presents a maximum likelihood estimation of the ultimate bond strength for soil nails in clays. Both uncensored and censored ultimate bond strength data for soil nails are collected from the literature. Based on the concept of maximum likelihood, a log-likelihood function is constructed for estimating the mean and coefficient of variation (COV) of the ultimate bond strength jointly using the two types of data. The mean and COV are determined as the pair that maximises the log-likelihood function. Two distribution models (normal and lognormal) are used for the estimation. A comparison of the relative competence between the two candidate distribution models that are adopted for describing the collected uncensored and censored data is performed using the Bayesian Information Criterion. Example designs of soil nail walls against internal pullout limit state of nails and overall stability limit state are provided to demonstrate the benefit of taking censored data into account for estimation of the ultimate bond strength of soil nails.     

基于北京二号与地理国情数据的林地提取

由于地理国情林地数据不包含实地面积小于400 m²的树木或四旁单排林,若仅利用地理国情的林地数据统计区域森林覆盖率,将对四旁树面积较大地区的林地统计结果产生较大误差。为提取区域内准确的林地覆盖与空间分布状况,本文借助地理国情地表覆盖数据,提出了一种基于北京二号高分辨率遥感影像的林地提取方法。首先,根据遥感影像光谱特征,将研究区按植被、道路、铁路、建筑用地进行地类划分,并基于遥感影像进行各地类的样本提取,通过可分离检验的样本利用最大似然分类提取研究区内植被覆盖范围;然后,借助地理国情地表覆盖数据,使用叠置分析剔除误分、错分地类,得到区域林地的空间分布。试验结果表明：(1)研究区内林地覆盖率为20.3%,尚未满足北京新一轮林地规划需求;(2)地理国情地表覆盖数据内林地面积占提取林地总面积的54.03%,说明在部分地区使用本文方法对地理国情林地数据进行补充是有必要的。通过将试验结果与遥感影像进行目视比对并结合外业调查结果发现,提取的林地空间分布情况与实际分布基本相符。本文为地理国情的应用提供了一种新方法,研究结果可辅助区域的绿色发展规划,有助于构建科学的生态空间格局。     

Mixture model based multivariate statistical analysis of multiply censored environmental data

Environmental data are commonly constrained by a detection limit (DL) because of the restriction of experimental apparatus. In particular due to the changes of experimental units or assay methods, the observed data are often cut off by more than one DL. Measurements below the DLs are typically replaced by an arbitrary value such as zeros, half of DLs, or DLs for convenience of analysis. However, this method is widely considered unreliable and prone to bias. In contrast, maximum likelihood estimation (MLE) method for censored data has been developed for better performance and statistical justification. However, the existing MLE methods seldom address the multivariate context of censored environmental data especially for water quality. This paper proposes using a mixture model to flexibly approximate the underlying distribution of the observed data due to its good approximation capability and generation mechanism. In particular, Gaussian mixture model (GMM) is mainly focused in this study. To cope with the censored data with multiple DLs, an expectation–maximization (EM) algorithm in a multivariate setting is developed. The proposed statistical analysis approach is verified from both the simulated data and real water quality data.