Addressing Conditioning Data in Multiple-Point Statistics Simulation Algorithms Based on a Multiple Grid Approach

Multiple-point statistics (MPS) allows simulations reproducing structures of a conceptual model given by a training image (TI) to be generated within a stochastic framework. In classical implementations, fixed search templates are used to retrieve the patterns from the TI. A multiple grid approach allows the large-scale structures present in the TI to be captured, while keeping the search template small. The technique consists in decomposing the simulation grid into several grid levels: One grid level is composed of each second node of the grid level one rank finer. Then each grid level is successively simulated by using the corresponding rescaled search template from the coarse level to the fine level (the simulation grid itself). For a conditional simulation, a basic method (as in snesim) to honor the hard data consists in assigning the data to the closest nodes of the current grid level before simulating it. In this paper, another method (implemented in impala) that consists in assigning the hard data to the closest nodes of the simulation grid (fine level), and then in spreading them up to the coarse grid by using simulations based on the MPS inferred from the TI is presented in detail. We study the effect of conditioning and show that the first method leads to systematic biases depending on the location of the conditioning data relative to the grid levels, whereas the second method allows for properly dealing with conditional simulations and a multiple grid approach.     

基于遗传算法的流域退水曲线的研究

针对手绘推求流域退水曲线的不足,本文提出了一种基于遗传算法推求流域退水曲线的优化方法.可方便快捷的推求出较优的流域退水曲线,使得预报值与实测值误差最小;克服了传统绘线法费时、人为性较大的缺点,为流域退水曲线的推求提供了一种新的思路.实例表明,该方法计算速度快,预报精度高,也体现了遗传算法的全局寻优能力.算法也可编译成通用性的操作程序,推广应用于其他流域退水曲线的推求.     

基于遗传算法最短路径问题的探讨

对用遗传算法求解最短路径问题作了有益的尝试，详细分析了求解最佳路径的遗传算法的构成要素，提出了一种新的交叉算子，并且论证了算法参数对结果的影响。通过仿真实验，给出了算法的主要性能参数，证明了算法的可行性。并指出了遗传算法求解最短路径问题的不足之处。     

从水文行业统计看水文事业发展

全国水文统计对制订水文事业发展规划和指导全国水文行业管理工作具有重要意义。本文根据《全国水文统计年报》,对比分析"十五"和"十一五"期间我国水文站网、设施设备、从业人员、经费投入等行业发展重要指标的变化情况。结果表明,水文站网向布局合理、项目齐全、功能完善的体系发展;水文基础设施建设不断加强,测报设施整体水平明显提升,先进仪器设备推广力度加大,水文测验方式和技术手段由传统方式向现代化方式转变;从业人员队伍整体素质不断提高,结构不断优化;水文经费投入大幅增加,为水文基础设施建设和水文业务工作开展提供了重要保障。"十五"和"十一五"期间,我国水文事业得到了健康快速发展,水文现代化水平逐步提升,水文测报和信息服务能力显著提高,为经济社会发展做出了重要贡献。     

基于遍历搜索算法的水文地质参数优化求解

为了解决传统的Theis配线法在求参过程中无法利用全部抽水试验数据、手动配线效率较低、求参过程受人为主观因素影响较大等问题,利用抽水试验数据,以Theis公式和叠加原理为理论基础,以理论计算降深与实测降深的Nach-Sutcliffe效率系数值达到最大为目标函数,基于Matlab软件编程,再利用遍历搜索算法对导水系数（T）、贮水系数（S）在其对应范围内进行遍历,实现了水文地质参数的自动精确求解。将遍历搜索算法应用于2个抽水试验实例的水文地质参数求解,并与传统求参方法的计算结果进行比较分析。结果表明：利用遍历搜索算法求参的计算结果与传统求参方法的计算结果相近,表明利用遍历搜索算法求解水文地质参数有效可靠;2个抽水实例利用遍历搜索算法得到的参数对应的理论计算降深与实测降深的Nach-Sutcliffe效率系数值分别为0.996 5、0.970 8,且相比传统的求参方法而言更接近1.000 0,说明其拟合程度更好。     

Parallel Multiple-Point Statistics Algorithm Based on List and Tree Structures

Multiple-point statistics are widely used for the simulation of categorical variables because the method allows for integrating a conceptual model via a training image and then simulating complex heterogeneous fields. The multiple-point statistics inferred from the training image can be stored in several ways. The tree structure used in classical implementations has the advantage of being efficient in terms of CPU time, but is very RAM demanding and then implies limitations on the size of the template, which serves to make a proper reproduction of complex structures difficult. Another technique consists in storing the multiple-point statistics in lists. This alternative requires much less memory and allows for a straightforward parallel algorithm. Nevertheless, the list structure does not benefit from the shortcuts given by the branches of the tree for retrieving the multiple-point statistics. Hence, a serial algorithm based on list structure is generally slower than a tree-based algorithm. In this paper, a new approach using both list and tree structures is proposed. The idea is to index the lists by trees of reduced size: the leaves of the tree correspond to distinct sublists that constitute a partition of the entire list. The size of the indexing tree can be controlled, and then the resulting algorithm keeps memory requirements low while efficiency in terms of CPU time is significantly improved. Moreover, this new method benefits from the parallelization of the list approach.     

Non-stationary Geostatistical Modeling Based on Distance Weighted Statistics and Distributions

A common assumption in geostatistics is that the underlying joint distribution of possible values of a geological attribute at different locations is stationary within a homogeneous domain. This joint distribution is commonly modeled as multi-Gaussian, with correlations defined by a stationary covariance function. This results in attribute maps that fail to reproduce local changes in the mean, in the variance and, particularly, in the spatial continuity. The proposed alternative is to build local distributions, variograms, and correlograms. These are inferred by weighting the samples depending on their distance to selected locations. The local distributions are locally transformed into Gaussian distributions embedding information on the local histogram. The distance weighted experimental variograms and correlograms are able to adapt to local changes in the direction and range of spatial continuity. The automatically fitted local variogram models and the local Gaussian transformation parameters are used in spatial estimation algorithms assuming local stationarity. The resulting maps are rich in nonstationary spatial features. The proposed process implies a higher computational effort than traditional stationary techniques, but if data availability allows for a reliable inference of the local distributions and statistics, a higher accuracy of estimates can be achieved.     

基于次序统计量理论的洪水频率分析方法研究

针对目前参数估计方法存在稀遇洪水频率设计值偏大的问题,提出采用基于数值次序统计量期望值的适线法计算洪水频率设计初始值;针对目前参数估计方法存在常遇洪水频率设计值偏小的问题,提出采用周文德公式修正目前频率设计偏小的情形,计算洪水频率设计修正值;针对目前传统方法计算洪水频率设计值抽样误差大的问题,提出采用基于数值次序统计量标准差的方法计算洪水频率设计保证值。定量分析表明,提出的基于数值次序统计量期望值的优化适线法具有良好的无偏性和有效性;寸滩站洪水频率设计修正值大于频率设计初始值,且两者偏差随着频率减小而减小;寸滩站洪水频率设计保证值明显大于修正值。     

基于遗传算法的土钉支护结构优化设计

将遗传算法用于基坑土钉支护优化设计中,分别用极限平衡法和有限元法进行优化设计,并对原设计、基于极限平衡分析的优化结果和基于有限元分析的优化结果进行比较,得出合理的土钉支护结构设计参考结论。     

基于DEM不同路径算法的沟壑密度提取

沟壑密度是评价小流域沟蚀程度的重要指标,同时也是反映地表破碎程度的因子。采用合理的汇流阈值设置方法,在黄土高原县南沟流域,通过基于坡向流量分配的多流向算法(DEMON)和传统的单流向算法D8实现沟壑密度的提取。结果表明:多流向算法和单流向算法都能提取较合适的沟壑密度,其中多流向算法提取的结果更好一些。因此,本研究对地表破碎程度的描述和当地地形地貌的反映有重要的意义。     

抽水试验资料的遗传算法反演水文地质参数

基于MATLAB遗传工具箱的遗传算法是一种借鉴生物界自然选择和自然遗传机制的全局最优化随机搜索算法。它以其简单通用、鲁棒性强、适于并行处理及高效等显著特点,在各领域得到了广泛的应用。结合抽水试验实例采用遗传算法反演水文地质参数,并将所求参数与配线法和直接图解法所得参数进行对比分析。结果显示,遗传算法所求参数的计算降深与实测降深吻合程度高,方便快捷,不失为一种有效的水文地质参数求解方法。     

基于因子分析的岩石可钻性指标分析

岩石可钻性级别的准确划分是提高钻进效率的有效措施之一,但因其指标极多,故这项工作至今没有圆满解决.传统的方法是通过直接测定岩石的各项物理力学性质来综合判定岩石的可钻性,但这种方法有两大缺陷.首先,各项数据之间数量级和量纲的差距极大;其次,各项数据之间存在很高的相关性,直接使用原始数据判定可钻性会带来误差.用标准差化的方法对原始数据预处理可以消除数量级和量纲的差距.利用多元统计中因子分析模型则可以将原始数据分类构成少数综合因子,再利用数学变换将综合因子转化为综合指标,最终不仅达到降低原始数据维数,简化分析计算的目的,而且综合指标之间的低相关性也避免了原始数据间高相关性带来的误差.     

Training Image Free High-Order Stochastic Simulation Based on Aggregated Kernel Statistics

Mathematical Geosciences - A training image free, high-order sequential simulation method is proposed herein, which is based on the efficient inference of high-order spatial statistics from the...     

基于AJAX技术实现搜索引擎中的搜索提示功能

在搜索引擎中,当用户输入搜索关键字时,客户端借助AJAX技术,会自动向服务器发送请求.通过异步通信,查询到相关的关键字并及时提示用户.这样用户就能很快找到所要搜索的内客,节省了大量的时闻.该技术能在全文搜索引擎中得到充分地应用,交互性强,用户满意度高.     

基于概率统计的可拓学分析方法在边坡岩体质量分级中的应用

在可拓学理论基础上添加了统计学思想,形成了一种基于概率统计的可拓学分析方法。以延边州和龙市红旗河引水工程项目为例,通过Matlab软件,采用蒙特卡洛模拟,将每个对象对应的因素值进行模拟,产生出服从一定分布的随机待评物元;再利用岩体边坡稳定性等级和影响因子,构造出经典域和节域物元,借助物元和可拓中的关联函数,建立起分析对象隶属于不同类别的概率值。利用此概率值,确定边坡岩体质量分级,并提出对工程设计和建设中的支护建议。对象2的最大概率值所属的类别为Ⅱ类,但对象2属于Ⅲ类的概率值为27%,由于工程采样存在的随机性,将对象2划分为Ⅲ类可以确保其安全性。     

Validation Techniques for Geological Patterns Simulations Based on Variogram and Multiple-Point Statistics

Traditional simulation methods that are based on some form of kriging are not sensitive to the presence of strings of connectivity of low or high values. They are particularly inappropriate in many earth sciences applications, where the geological structures to be simulated are curvilinear. In such cases, techniques allowing the reproduction of multiple-point statistics are required. The aim of this paper is to point out the advantages of integrating such multiple-statistics in a model in order to allow shape reproduction, as well as heterogeneity structures, of complex geological patterns to emerge. A comparison between a traditional variogram-based simulation algorithm, such as the sequential indicator simulation, and a multiple-point statistics algorithm (e.g., the single normal equation simulation) is presented. In particular, it is shown that the spatial distribution of limestone with meandering channels in Lecce, Italy is better reproduced by using the latter algorithm. The strengths of this study are, first, the use of a training image that is not a fluvial system and, more importantly, the quantitative comparison between the two algorithms. The paper focuses on different metrics that facilitate the comparison of the methods used for limestone spatial distribution simulation: both objective measures of similarity of facies realizations and high-order spatial cumulants based on different third- and fourth-order spatial templates are considered.     

基于等高线簇的沟谷线提取算法的研究与实现

从数字化地形资料中自动提取沟谷线的技术在水文分析、工程领域等具有重要的意义。在对现有的沟谷线自动提取的基础上,提出一种简单准确的沟谷线提取的方法。选取某一区域的矢量地形图进行试验与实际地形进行对比,结果表明沟谷线提取方法是准确的。     

基于紧支双正交小波的多分辨率分析模型与视觉相关三维地表显示

通过设计具有线性相位和对称性的紧支双正交小波来提取同一地形区域上的多分辨分析模型,并建立基于四叉树结构的数据库.结合人眼视觉的限制,对敏感地区的地表用高分辨率数据显示,对不敏感地区的地表则用低分辨率数据显示.这样图像的数据量就会大大减少,可以加快三维地表模型的显示速度.     

基于支持向量机分类算法的湖泊水质评价研究

支持向量机（SVM）是由Vapnik等人提出的建立在统计学习理论基础上的一种小样本机器学习方法,最初用于解决二分类问题。由于使用结构风险最小化原则代替经验风险最小化原则,使它较好地解决了小样本情况下的学习问题。又由于采用了核函数思想,使它将非线性问题转化为线性问题来解决,降低了算法的复杂度。利用支持向量机多类分类算法,构建湖泊水环境评价模型。实验结果表明,该方法能够正确地对湖泊水环境质量进行分类评价。     

基于遗传算法的扩散波洪水演算参数的确定方法

大量的理论分析和实际洪水演算表明,扩散波方法是一种既具有足够精度又相对简单的一类洪水演算方法。以线性扩散波方程在自由下边界条件下的解析解为例,利用遗传算法来确定扩散波方程的参数。遗传算法和一般的优化算法不同,它具有全局寻优能力,一般能得到问题的最优解或准最优解,是一类优秀的非线性函数优化方法。实例计算结果表明,采用遗传算法所得到的参数精度较高,可以类推到其它水文模型的参数率定中去。