抗差最小二乘配置在数字化地图几何纠正中的应用讨论

抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。     

基于岭估计的有理多项式参数求解方法

在使用最小二乘法解算卫星遥感影像的RPC参数时,如果控制点非均匀分布或模型过度参数化,其法方程系数矩阵很容易产生病态,获得的解将偏离真值,甚至得到错误的解.使用岭估计可改善法方程的状态,保证解稳定.采用岭估计方法,通过所获取的不同岭参数对SPOT和QuickBird影像进行实验,证实L曲线法是一种稳定的、有效的岭参数确定方法,可显著提高RPC参数的解算精度.     

西藏札达盆地控盆断裂有限元数值模拟

札达盆地是喜马拉雅构造带中的一个山间断陷盆地,其演化过程与盆地两侧的控盆构造密切相关。对控盆断裂的构造应力场进行模拟计算,将有助于进一步深化对本区构造控盆的认识。因此,在对盆地构造地质进行详细调查的基础上,结合本区的深部地质与地球物理资料,对札达盆地控盆断裂的构造应力场进行了模拟。计算结果表明,札达盆地的演化明显受盆地两侧边界断裂的控制,札达盆地是在整体南北向挤压应力的作用下,不同块体差异隆升作用的结果。其南侧的控盆断裂为北倾的正断层,北侧的控盆断裂为南倾的逆断层,二者共同形成了南降北升的翘板式断陷盆地运动过程,是喜马拉雅地块在陆内汇聚挤压构造环境中构造应力场调整的一种方式。     

应用探地雷达探测活动断层

在浅覆盖区采用探地雷达探测地震活动断层。通过实验确定出最佳的采集参数和数据处理流程,在雷达剖面上,能够清晰地显示出断层上部的形态特征、上断点埋深和岩土分层。结合钻孔资料,利用雷达剖面上对第四系覆盖的分层结果和上断点所在的层位可以分析和评价断层的活动性。     

Bayesian estimation of seismic hazard for two sites in Switzerland

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.     

参数的期望估计及其在形变分析中的应用

利用“参数的期望估计”能准确定位、定量粗差及参数的期望估计不受粗差影响折特殊性质,寻找地壳变形区域和不变形区域,以确定拟稳点,进而进行拟稳变换,分析地菜变,将是一种有效方法。     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.     

On the physical model of earthquake precursor fields and the mechanism of precursors＇timespace distribution──origin and evidences of the strong body earthquake──generating model

Ｏｎｔｈｅｐｈｙｓｉｃａｌｍｏｄｅｌｏｆｅａｒｔｈｑｕａｋｅｐｒｅｃｕｒｓｏｒｆｉｅｌｄｓａｎｄｔｈｅｍｅｃｈａｎｉｓｍｏｆｐｒｅｃｕｒｓｏｒｓ＇ｔｉｍｅｓｐａｃｅｄｉｓｔｒｉｂｕｔｉｏｎ──ｏｒｉｇｉｎａｎｄｅｖｉｄｅｎｃｅｓｏｆ　ｔｈｅｓｔｒｏｎ...     

成都城市发展对热岛强度影响的主成份回归分析

本文对成都市总人口、建成区面积等11个因子、作了主成份回归L-S估计和M-估计,讨论了成都城市发展对“热岛”强度的主要影响因子。结果表明,城区房屋建筑面积及总人口数是影响城市气候(气温)的主要因子,其次为城市人口总户数、建成面积等。 文中,对回归方程进行了拟合计算,回归效果比较满意(尤其是稳健回归)。