Combination of Dependent Realizations Within the Gradual Deformation Method

Gradual deformation is a parameterization method that reduces considerably the unknown parameter space of stochastic models. This method can be used in an iterative optimization procedure for constraining stochastic simulations to data that are complex, nonanalytical functions of the simulated variables. This method is based on the fact that linear combinations of multi-Gaussian random functions remain multi-Gaussian random functions. During the past few years, we developed the gradual deformation method by combining independent realizations. This paper investigates another alternative: the combination of dependent realizations. One of our motivations for combining dependent realizations was to improve the numerical stability of the gradual deformation method. Because of limitations both in the size of simulation grids and in the precision of simulation algorithms, numerical realizations of a stochastic model are never perfectly independent. It was shown that the accumulation of very small dependence between realizations might result in significant structural drift from the initial stochastic model. From the combination of random functions whose covariance and cross-covariance are proportional to each other, we derived a new formulation of the gradual deformation method that can explicitly take into account the numerical dependence between realizations. This new formulation allows us to reduce the structural deterioration during the iterative optimization. The problem of combining dependent realizations also arises when deforming conditional realizations of a stochastic model. As opposed to the combination of independent realizations, combining conditional realizations avoids the additional conditioning step during the optimization process. However, this procedure is limited to global deformations with fixed structural parameters.     

Sensitivity Analysis of a Feedforward Neural Network for Considering Genetic Mechanisms of Kuroko Deposits

Exploration for volcanogenic massive sulfide deposits of the kuroko-type is underway in many places. Clarifying the spatial patterns of the metals in kuroko deposits will be useful for understanding their genetic mechanisms and for future exploration of such types of deposits. This study represents a spatial distribution analysis on the contents of principal metals of kuroko deposits: Cu, Pb, and Zn, in the Hokuroku district, northern Japan, by a feedforward neural network and 1917 sample data at 143 drillhole sites. The network, which consists of three layers, was trained by the principle of SLANS in which the numbers of neurons in the middle layer and training data are changed to improve estimation accuracy. Using the weight coefficients connecting adjacent neurons, sensitivity analysis of the neural network was carried out to identify factors influencing spatial distributions of the three metals. The coordinates depth (z) direction, Bouguer gravity, and specific lithology such as dacite were determined to be influencing factors. The high frequency of the z coordinate signifies that the metal contents differ to a large extent by depth. The sensitivity vector was defined using sensitivity coefficients for x, y, and z coordinates of an estimation point. We determined that the directions of large vectors were different inside and outside of the Hanawa-Ohdate area. This characteristic is considered to originate from the differences in the permeability of fractures that became the paths for rising ore solutions, and the depths that the solutions mixed with sea water.     

基于信息块法的矢量符号库的建立和符号化实现

基于试验成果，详细介绍了基于信息块法的矢量地图符号库的建立和空间信息的符号化。     

无拓扑矢量数据快速压缩算法的研究与实现

首先论述传统矢量数据压缩算法：道格拉斯—普克法，分析将其应用于多边形边界数据压缩所造成的图形失真现象，在此基础上提出一种针对无拓扑矢量数据的快速压缩算法，并在MapInfo环境中实现该算法。     

Spectral and Multiscale Signal-to-Noise Thresholding of Spherical Vector Fields

The basic concepts of spectral and multiscale selective reconstruction of (geophysically relevant) vector fields on the sphere from error-affected data is outlined in detail. The reconstruction mechanism is formulated under the assumption that spectral as well as multiscale approximation is well-representable in terms of only a certain number of expansion coefficients at the various resolution levels. It is shown that spectral denoising by means of orthogonal expansions in terms of vector spherical harmonics reflects global a priori information of the noise (e.g., in form of a covariance tensor field), whereas multiscale signal-to-noise thresholding can be performed under locally dependent noise information within a multiresolution analysis in terms of spherical vector wavelets. An application of the multiscale formalism to Earth's magnetic field determination is presented.     

Web环境下SVG地图浏览器的设计与实现

SVG是近年来发展起来的基于XML的用于描述矢量图形、图像的标准规范，该规范的制定对网上矢量地图数据的共享具有十分重要的意义，基于SVG的矢量地图十分有利于地理空间数据的传播。文中首先分析了目前Web环境下矢量地图发布存在的问题，之后介绍了SVG的有关情况，最后基于Adobe的SVG Vie—wer2．0设计并实现了一个SVG地图浏览器，着重研究了3个问题，即矢量地图数据在SVG文档中的组织与编码，地图浏览器界面的设计以及若干地图操作功能的实现。     

定量分析几种Q矢量

结合1991年7月5日20:00～6日20:00一次典型的江淮梅雨锋暴雨过程，从台站实际业务工作需要考虑，细致、具体地比较分析了850 hPa、700 hPa及500 hPa 3个层次的准地转 Q 矢量散度场、半地转 Q 矢量散度场、非地转 Q 矢量散度场及湿 Q 矢量散度场与相应时刻地面降水场对应关系的差异，同时还针对每一种 Q 矢量，将其在850 hPa、700 hPa及500 hPa 3个层次的散度场对同时刻降水场的反映能力进行了比较。在定量比较的基础上，得到了对4种 Q 矢量诊断特性的具体认识:（1）在整个梅雨锋暴雨过程中，3个层次的半地转 Q 矢量散度场及准地转 Q 矢量散度场对雨区的反映能力较小，而非地转 Q 矢量的散度场和湿 Q 矢量的散度场对雨区的反映能力明显较前二者大，尤其是湿 Q 矢量散度场在每个层次的诊断能力基本都大于相应层次的其它 Q 矢量的散度场。（2）对于每一种 Q 矢量而言，基本都是在700 hPa的散度场与雨区的对应关系好于各自在850 hPa和500 hPa的散度场，尤其是700 hPa湿 Q 矢量散度辐合场对同时刻梅雨锋暴雨的强度及落区都有很好的指示作用。最后，基于理论的角度对各 Q 矢量的诊断特性进行了较为深入地探讨和比较分析，明确地指出了4种 Q 矢量存在理论前提上的差异。     

全球观测应力场的短波分量分析

世界应力图(WSM，World Stress Map)计划的应力指标，目前已累积数据共计10 920个，这些应力指标代表了该地区最大水平主应力的实际观测方向；与此同时，可以假定全球各个板块的绝对运动方向表征了相应各板块的最大水平主应力方向的长波分量．根据应力场的叠加原理，得到由该地区局部构造运动等因素贡献的短波分量的相对大小和方向．将全球划分成2.52.5的基本单元，对每个单元的WSM数据进行加权统计分析，得到其平均应力观测取向，利用HS2-NUVEL1全球绝对板块运动模型计算应力场的长波分量；平均观测应力取向和长波分量取向之间的夹角，决定了相应短波分量相对于观测应力场的大小及其取向的范围，并反映了特定研究地区局部应力场对总应力场的贡献程度．本文的计算结果表明，全球板块的绝大部分地区及各板块的平均效果，长波分量与短波分量对观测应力场的贡献程度相当．对于某些大陆板块内部，局部构造活动对观测应力场的贡献起到重要作用，因而控制着地震的孕育与发生．      

特征根估计

介绍的特征根估计是主成分估计的推广，其特点是把因变量和自变量放在一起来考虑它闪的特征根和特征向量，而主成分估计只限于自变量。因此，这个新提出的有偏估计引起广泛的兴趣，言语中在阐述其理论的基础上，结合实例说明这种有偏估计和主成分估计一样可以改进最小二乘估计。