An Improved Perturbation Mechanism for Simulated Annealing Simulation

Simulated annealing (SA) is being increasingly used for the generation of stochastic models of spatial phenomena because of its flexibility to integrate data of diverse types and scales. The major shortcoming of SA is the extensive CPU requirements. We present a perturbation mechanism that significantly improves the CPU speed. Two conventional perturbation mechanisms are to (1) randomly select two locations and swap their attribute values, or (2) visit a randomly selected location and draw a new value from the global histogram. The proposed perturbation mechanism is a modification of option 2: each candidate value is drawn from a local conditional distribution built with a template of kriging weights rather than from the global distribution. This results in accepting more perturbations and in perturbations that improve the variogram reproduction for short scale lags. We document the new method, the increased convergence speed, and the improved variogram reproduction. Implementation details of the method such as the size of the local neighborhood are considered.     

Accounting for Estimation Optimality Criteria in Simulated Annealing

This paper presents both estimation and simulation as optimization problems that differ in the optimization criteria, minimization of a local expected loss for estimation and reproduction of global statistics (semivariogram, histogram) for simulation. An intermediate approach is proposed whereby an initial random image is gradually modified using simulated annealing so as to better match both local and global constraints. The relative weights of the different constraints in the objective function allow the user to strike a balance between smoothness of the estimated map and reproduction of spatial variability by simulated maps. The procedure is illustrated using a synthetic dataset. The proposed approach is shown to enhance the influence of observations on neighboring simulated values, hence the final realizations appear to be better conditioned to the sample information. It also produces maps that are more accurate (smaller prediction error) than stochastic simulation ignoring local constraints, but not as accurate as E-type estimation. Flow simulation results show that accounting for local constraints yields, on average, smaller errors in production forecast than a smooth estimated map or a simulated map that reproduces only the histogram and semivariogram. The approach thus reduces the risk associated with the use of a single realization for forecasting and planning.     

随机介质理论在深基坑稳定性分析中的应用

使用矿业工程中广为应用的随机介质理论和方法,计算深基坑开挖引起的地表及土体变形,并据此探讨深基坑边坡的稳定性。     

“三江”地区北段某多元素异常带的特征及找矿前景分析

１∶２０万区域化探扫面圈定出“三江”地区北段某多元素异常带,呈北西南东向条带状展布。由Ｗ、Ｍｏ、Ｃｕ、Ｂｉ、Ｕ、Ｓｎ、Ａｇ、Ｃｄ、Ｐｂ、Ｚｎ、Ａｓ、Ｂａ、Ｈｇ、Ａｕ等高中低温热液成矿与伴生元素组成于一体,具典型的浓度分带与组分分带特征。它位于玉龙斑岩铜矿带北侧,对该异常带的解剖,具重要的理论与实际意义。     

区域地下水溶质运移随机理论的研究与进展

在总结近年来国内外区域地下水溶质运动研究的基本理论、方法和部分成果的基础上,论述了溶质在大区域运动的主要影响因素为区域介质的空间变异性。首先总结了野外条件下饱和介质和非饱和介质土壤渗透性能的空间变异性结果,由于野外渗透介质严重的空间变异性,研究溶质在野外条件下的运动采用了随机理论方法。基于Lagrange方法和Euler方法,研究结果表明,在渗透系数为对数正态二阶平稳及一阶扰动近似条件下,平均浓度满足对流－弥散方程,方程中宏观弥散度决定于介质渗透性能的统计特征,总结了一系列宏观弥散系数的表达形式,在此基础上,指出了需要进一步研究的问题。     

A Lagrangian stochastic model for the trajectories of particle pairs and its application to the prediction of concentration variance within plant canopies

A simple Lagrangian stochastic model for the trajectories of particle pairs in high Reynolds-number turbulent flows is presented. In this model, the velocities of particle pairs are initially correlated but subsequently each particle moves independently. The independent single-particle trajectories are simulated using Thomson's model [J. Fluid Mech. 180, 529–556, 1987]. This two-particle model exactly satisfies the well-mixed condition for Gaussian turbulence when length scales, characterizing the two-point Eulerian velocity correlation function, vanish. Temperature variances, due to heat released as a passive scalar from an elevated plane source, within a model plant canopy (Coppin et al. Boundary Layer Meteorol. 35, 167–191, 1986) are shown to be well predicted by the model. It is suggested that for strongly inhomogeneous flows, the two-point Eulerian velocity function is of secondary importance in determining the simulated trajectories of particle pairs compared to the importance of ensuring satisfaction of the two-to-one constraint (Borgas and Sawford. J. Fluid Mech. 279, 69–99, 1994); i.e ensuring that one-particle statistics obtained from the two-particle model are the same as those obtained from the corresponding one-particle model. Limitations of this modelling approach are discussed.     

贵州省1：200000区域化探数据入库及检索应用

本文是一份数据入库方法及检索应用的总结。文中主要介绍了利用计算机进行化探数据入库及检索应用。入库数据可进行标准图幅检索、任意区域检索等多条件数据检索，检索出的数据可作多种化探数据处理，并绘制等值线图、色块图等图形及图像。此项技术经济投入少，能及时检索数据、处理数据、显示及打印图形、图像，以指导找矿及勘探，具有一定的实用价值。     

一种新的北斗Klobuchar模型及其精度分析

针对传统Klobuchar模型电离层延迟修正精度不高的问题,提出一种新的Klobuchar模型,以提高北斗导航系统的精度。利用欧洲定轨中心CODE的全球格网数据作为参考,使用松弛搜索法分别对覆盖中国区域的格网点和9个测站的观测数据进行算例分析。比较两种方法得出,新模型的修正精度相对于广播模型有大幅提高;新模型预报7d内的电离层时延值修正效果也比广播模型有明显改善;格网点上的平均修正精度从67.89%提高到78.44%,观测数据的平均修正精度从69.81%提升至82.34%。     

方程误差系统的多新息辨识方法

多新息方法可以用于线性系统和非线性系统的自适应滤波、参数估计、自校正控制、自适应故障检测与诊断等.线性系统包括两种基本类型:方程误差类系统和输出误差类系统.本文将多新息辨识应用到方程误差滑动平均(EEMA)系统(即CARMA系统),研究多新息增广随机梯度算法和多新息增广最小二乘算法,应用到方程误差自回归滑动平均(EEARMA)系统(即CARARMA系统),提出基于分解的多新息广义增广随机梯度算法和基于分解的多新息广义增广最小二乘算法,以及基于滤波的多新息广义增广随机梯度算法和基于滤波的多新息广义增广最小二乘算法.     

金融领域的随机建模与基于软件R的Monte Carlo模拟(4):随机微分方程模型

主要研究线性随机微分方程模型,为此定义Itô随机微积分,建立Itô公式.鉴于研究的重点是利用R软件进行数值模拟,所以详细讨论了过去10多年来随机微分方程数值解的研究.