年最大洪峰流量的P-Ⅲ型分布拟蒙特卡罗随机模拟研究

随机模拟水文序列需要大量的随机数,而且利用传统的伪随机数模拟结果存在统计性质不好等缺陷.采用拟蒙特卡罗方法生成的拟随机数序列,模拟得到的年最大洪峰流量序列的统计性质较好,并且误差随着模拟样本长度的增加收敛很快.可以采用基于拟蒙特卡罗的随机模拟技术来得到所需样本长度的年最大洪峰流量资料.     

蒙特卡罗法在煤层气资源量计算中的应用

将蒙特卡罗(Monte-Carlo)法引入煤层气资源量计算,可弥补容积法视各参数为常数的不足。重点论述了蒙特卡罗法用于煤层气资源量计算的主要算法和函数实现,包括参数选择、分布函数确定、伪随机数的产生以及对应伪随机数参数值的确定。利用上述算法自主开发了蒙特卡罗法软件。研究实例表明,在数据样本较多的情况下,该算法与容积法能保持较小误差范围且有更高的可信度。      

基于非周期伪随机序列的可控震源信号调制技术

从便于寻优的角度出发,给出了三元非周期伪随机序列的一种定义,提出了基于非周期伪随机序列的可控震源信号调制方法。该方法与二元m[CD*2]序列调制方法相比,不存在地震数据资源的浪费问题。三元非周期伪随机序列通常比相同长度的二元非周期伪随机序列具有更小的边峰主峰比。地震数值模拟结果表明,将具有较小边峰主峰比的三元非周期伪随机序列调制生成的信号作为地震勘探中可控震源的发射信号,其地震响应剖面的相关噪声要比相同长度的二元非周期伪随机序列调制情形有明显的减弱。     

一种伪随机信号混合编码及其在油气压裂智能实时监测系统中的应用

介绍了基于x×a~n与y×b~n序列的伪随机信号混合编码的实现方法、硬件动态加载过程,及其在四川威远某页岩气压裂监测工程中的应用。应用基于x×a~n与y×b~n序列的伪随机信号混合编码方法,可以设计出满足伪随机编码规则的组合形式的伪随机信号,并对波形进行编码,自动生成码流。基于这种编码的动态装载技术可以对大而长和较复杂的组合伪随机信号进行加载,为多种伪随机信号应用提供了一种便捷、通用的技术方法手段。     

蒙特卡罗法油气资源评价软件的设计与开发

根据有关资料，对比油气资源量评价的各种方法，详细论述了蒙特卡罗法在油气资源量评价中的应用原理和特点，从算法上解决了蒙特卡罗法的关键实现技术即伪随机数产生和随机数抽样问题。利用API设计编制了程序软件，完成了程序设计、算法实现、界面开发等工作，并应用于实际地区的资源评价工作，给出了实际算例。     

处理DEM中闭合洼地和平坦区域的一种新方法

数字高程模型(DEM)中的闭合洼地和平坦区域影响着流域排水网络的自动提取.目前已提出很多方法来处理这两种地形,但均针对已经形成的DEM单元网格进行处理,结果往往生成伪河道及平行河道.在回顾分析了这些方法存在的问题后,提出了一种新的处理方法,该法认为DEM中的闭合洼地和平坦区域是由于低质量的资料输入、生成DEM时的内插误差等引起的.通过增加输入地形高程信息,避免了DEM中平坦区域和闭合洼地的生成,从而使由DEM生成的河网与实际河网能够精确拟合.实例分析表明,该方法效果明显.     

一种简单方便的防拷贝程序设计方法——识别计算机的C语言程序设计

本文主要讨论一种特殊的Ｃ语言程序设计方法，这种程序能有效地对自身的关键模块加密，并能在运行时完成动态解密。该方法主要利用了“硬盘分区表”和最初安装在硬盘中程序自身的位置等信息，采用伪随机数加密法来实现。因所设计的程序具有识别计算机的能力，能有效地防止非法复制，从而保护软件制作者的知识产权和经济利益     

EL-5002计算器用法商讨(下)

本文前一部分我们讨论了用EL-5002计算器作某些数列求和及迭代计算等。在这一部分中我们准备让它作另一种类型的计算。这些计算主要与程序工作有关,包括十进制数与八进制数的互换,在数据库设计中研究数据散列地址的方案,以及伪随机数的产生等。下面先从讨论某些问题开始。     

冻土CT图像中环形伪影和射线束硬化伪影的成因及校正方法

冻土CT图像中不可避免地会出现环形伪影和射线束硬化伪影。为解决这些问题, 分析了两类伪影的特征和形成机理, 提出了降低伪影的硬件优化方案。首先, 通过改变X射线管电压, 以此改变X射线光通量来降低冻土CT图像的环形伪影。其次, 利用不同厚度的滤过材料, 将X射线中的低能射线预先过滤, 使得穿过冻土试样的X射线能谱范围变窄, 以此来降低射线束硬化伪影对试样的影响。对比分析结果表明： 将扫描电压提高到120 kV既能有效降低同类型冻土试样CT图像中的环形伪影, 又能保证图像的质量; 选用材质为2A12、 厚度为18 mm的航空铝材, 在扫描电压为120 kV、 扫描电流为230 mA的条件下可以有效抑制射线束硬化所造成的伪影。     

可控震源伪随机扫描信号的仿真研究

伪随机序列具有良好的的自相关函数,在地震勘探中具有广阔的应用前景,从提高伪随机扫描信号自相关函数性能出发,着重分析了与伪随机扫描信号自相关函数密切相关的重要参数。通过对仿真结果分析得出了载波频率及本原多项式阶次与其自相关函数之间的联系,并给出了伪随机扫描信号长度及幅值的选择原则。     

边坡模糊随机可靠性分析的模糊点估计法

在统计矩点估计法和模糊随机理论的基础之上,提出边坡工程模糊随机可靠性分析的模糊点估计法,将边坡稳定性极限状态方程由模糊随机集向普通随机集转化,然后利用点估计法求解边坡的可靠度指标。鉴于岩土体物理力学参数的近似分布类型,采用区别于梯形模糊数的正态模糊数对随机变量进行模糊随机化处理,使其更趋近于物理力学参数的近似分布类型。该方法考虑了各个力学参数的模糊性,计算结果更能反映边坡的真实工作状态。算例分析结果表明,该法使用简便,计算效率高,结果可靠,避免了传统分析方法的缺点,对复杂边坡或者功能函数为隐式表达的边坡工程可靠性分析具有很大的潜力,为边坡可靠性分析提供了一条新的途径,具有广泛的应用前景。     

On the pseudo cross-variogram

Normal cross-variograms cannot be estimated from data in the usual way when there are only a few points where both variables have been measured. But the experimental pseudo cross-variogram can be computed even where there are no matching sampling points, and this appears as its principal advantage. The pseudo cross-variogram may be unbounded, though for its existence the intrinsic hypothesis alone is not a sufficient stationarity condition. In addition the differences between the two random processes must be second order stationary. Modeling the function by linear coregionalization reflects the more restrictive stationarity condition: the pseudo cross-variogram can be unbounded only if the unbounded correlation structures are the same in all variograms. As an alternative to using the pseudo cross-variogram a new method is presented that allows estimating the normal cross variogram from data where only one variable has been measured at a point.     

On the pseudo cross-variogram

Normal cross-variograms cannot be estimated from data in the usual way when there are only a few points where both variables have been measured. But the experimental pseudo cross-variogram can be computed even where there are no matching sampling points, and this appears as its principal advantage. The pseudo cross-variogram may be unbounded, though for its existence the intrinsic hypothesis alone is not a sufficient stationarity condition. In addition the differences between the two random processes must be second order stationary. Modeling the function by linear coregionalization reflects the more restrictive stationarity condition: the pseudo cross-variogram can be unbounded only if the unbounded correlation structures are the same in all variograms. As an alternative to using the pseudo cross-variogram a new method is presented that allows estimating the normal cross variogram from data where only one variable has been measured at a point.     

Efficient Simulation of (Log)Normal Random Fields for Hydrogeological Applications

Two methods for generating representative realizations from Gaussian and lognormal random field models are studied in this paper, with term representative implying realizations efficiently spanning the range of possible attribute values corresponding to the multivariate (log)normal probability distribution. The first method, already established in the geostatistical literature, is multivariate Latin hypercube sampling, a form of stratified random sampling aiming at marginal stratification of simulated values for each variable involved under the constraint of reproducing a known covariance matrix. The second method, scarcely known in the geostatistical literature, is stratified likelihood sampling, in which representative realizations are generated by exploring in a systematic way the structure of the multivariate distribution function itself. The two sampling methods are employed for generating unconditional realizations of saturated hydraulic conductivity in a hydrogeological context via a synthetic case study involving physically-based simulation of flow and transport in a heterogeneous porous medium; their performance is evaluated for different sample sizes (number of realizations) in terms of the reproduction of ensemble statistics of hydraulic conductivity and solute concentration computed from a very large ensemble set generated via simple random sampling. The results show that both Latin hypercube and stratified likelihood sampling are more efficient than simple random sampling, in that overall they can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than the simple random sampling.     

稳定渗流条件下土坡稳定性分析的一种新方法

在提出随机角生成曲线滑动面方法的基础上,通过改变选定参数来搜索临界滑动面,对渗流作用下的不同士质边坡进行稳定性分析.考虑渗流效应时,将士体视为三种土条划分情况,并进行受力分析,推导出简化Janbu法中土条的浮力和渗透力计算公式.同时,对实际渗流场做出合理简化,以便应用于计算机编程.算例对比分析表明:①此方法计算出的最小...     

The FFT Moving Average (FFT-MA) Generator: An Efficient Numerical Method for Generating and Conditioning Gaussian Simulations

A fast Fourier transform (FFT) moving average (FFT-MA) method for generating Gaussian stochastic processes is derived. Using discrete Fourier transforms makes the calculations easy and fast so that large random fields can be produced. On the other hand, the basic moving average frame allows us to uncouple the random numbers from the structural parameters (mean, variance, correlation length, ... ), but also to draw the randomness components in spatial domain. Such features impart great flexibility to the FFT-MA generator. For instance, changing only the random numbers gives distinct realizations all having the same covariance function. Similarly, several realizations can be built from the same random number set, but from different structural parameters. Integrating the FFT-MA generator into an optimization procedure provides a tool theoretically capable to determine the random numbers identifying the Gaussian field as well as the structural parameters from dynamic data. Moreover, all or only some of the random numbers can be perturbed so that realizations produced using the FFT-MA generator can be locally updated through an optimization process.     

快速模拟退火算法在含水层参数识别中的应用

针对一般模拟退火算法收敛速度慢的缺陷,本文提出了含水层参数识别的快速模拟退火算法。它以广义Boltzmann-Gibbs统计理论为基础,采用依赖于温度的似Cauchy分布产生新的扰动模型,通过改变模型扰动、接收概率和降温方式来加快模拟退火算法的收敛速度。实例的计算结果表明,快速模拟退火算法不仅可行,而且求解精度高,收敛速度比其他算法快得多,是一种值得在实际中推广应用的高效的含水层参数识别方法。