KPZ方程与KPZ普适性简介

本文首先介绍KPZ (Kardar-Parisi-Zhang)普适类的物理背景,其中, Eden模型、黏性落体模型和KPZ方程这几类物理模型将被提及;其次,将考察一维KPZ方程的Cole-Hopf解以及几类收敛到一维KPZ方程的离散模型(如角落生长模型和定向聚合物模型等).     

一维Brusselator模型

用两种方法证明了一维Brusselator模型对应的Q过程非强遍历.对一个修正的一维Brusse—lator模型,证明了其对应的Q过程是强遍历的.应用其方法研究了一类扩展的分支过程,得到该过程强遍历的一个必要条件.     

一维可压缩Euler方程组的两个模型

作者考察了一维可压缩Euler方程组的两个模型.利用特征分解和Gronwall不等式,首先得到具有几何结构且绝热指数γ=3的一维可压缩Euler方程组L~∞模的一致有界性.进一步,考虑当绝热指数γ=-1时,一维非等熵可压缩Euler方程组的Cauchy问题.在适当的假设下,得到该系统的整体经典解.     

一维半导体流体动力学模型的局部有界解

本文讨论了能量方程是压力一密度关系的一维半导体流体动力学模型方程,通过把欧拉－泊松方程变成拟线性波动方程,利用拟线性波动方程的局部解存在性,得到一维半导体流体动力学模型的局部解,并且解是有界的。     

双随机环境下一维选举模型生存概率界的估计

本文用随机环境中随机游动的知识讨论了双随机环境中一维选举模型 ,给出了该模型生存概率界的估计 .     

移动荷载作用下黏弹性地基-Timoshenko梁振动响应对比分析

基于Fourier变换方法,对移动荷载作用下三维、二维和一维轨道-地基模型的振动响应特征进行了研究,将轨道视为Timoshenko梁,比较了不同速度和地基厚度下各计算模型之间的响应差异.研究结果表明:三维模型存在一个地基等效刚度,为波数和频率的函数.二维和三维模型的临界速度较为接近,但比一维地基梁模型要小得多.荷载速度小于地基临界速度时,三维模型的梁挠度幅值最小,二维模型次之,一维模型梁挠度最大.当荷载速度达到或超过临界速度时,二维模型的梁挠度幅值变得最大,此时三者的挠度时程曲线存在明显差别.二维和三维模型的地层水平位移幅值先随地基深度增加而增大,在某一深度达到最大值后随深度增加逐渐减小,竖向位移幅值则随深度的增加逐渐减小.     

Vasicěk随机利率模型下指数O-U过程的幂型期权鞅定价

研究了Vasicěk随机利率模型中一维标准Brown运动与资产价格服从指数Ornstein-Uhlenbeck过程中一维标准Brown运动的相关系数为ρ(-1≤ρ≤1)的情形下的幂型期权鞅定价问题.推广了基于Vasicěk随机利率模型下基于Black-Scholes公式的两种幂型期权定价问题.并利用Girsanov定理和等价鞅测度,给出了基于Vasicěk随机利率模型下服从指数Ornstein-Uhlenbeck过程的两种欧式幂型期权鞅定价公式.     

有交货时间限制的大规模实用下料问题

研究的是有交货时间限制的单一原材料下料问题(规模较大).对于一维下料问题,本文得到一个有各自交货时间的模型.针对该模型提出一种新的算法:DP贪婪算法.计算结果是总用料800根即可完成需求任务,材料利用率为99.6%.对于二维下料问题,在一维的基础上建立了二维的求解模型,运用我们自己设计的降维思想结合一维的DP贪婪算法,给出解决该模型的算法.计算结果是总用料451块即可完成需求任务,材料利用率位99.2%.算法设计时考虑了普遍的情况,所以算法在解决大多数实际下料问题,特别是大规模下料问题时是切实有效的.     

门限自回归模型的非参数估计

对一维一阶一个门限的ＴＡＲ模型，通过模型所构成的Ｍａｒｋｏｖ链的遍历性，得到了其核密度估计的渐近无偏性，均方相容性和渐近正态性     

二维动态规划模型及其在陕西省七·五技改规划中的应用

在—般情况下,动态规划的阶段变量是一维的。但在实际工作中存在一类多阶段决策问题,由于这类问题的约束条件较多,造成状态变量的转移方向比较复杂,因而无法用一维动态规划模型求解。本文将动态规划数学模型中的阶段变量扩展到二维,通过建立二维动态规划模型对以上问题进行了研究。并且应用所建立的模型求解了一个实际的资源分配问题。     

Conservation laws for two-phase filtration models

The paper is devoted to investigation of group properties of a one-dimensional model of two-phase filtration in porous medium. Along with the general model, some of its particular cases widely used in oil-field development are discussed. The Buckley–Leverett model is considered in detail as a particular case of the one-dimensional filtration model. This model is constructed under the assumption that filtration is one-dimensional and horizontally directed, the porous medium is homogeneous and incompressible, the filtering fluids are also incompressible. The model of “chromatic fluid” filtration is also investigated. New conservation laws and particular solutions are constructed using symmetries and nonlinear self-adjointness of the system of equations.     

Neural net versus classical models for the detection and localization of leaks in pipelines

Four models of a pipeline are compared in the paper: a nonlinear distributed-parameter model, a linear distributed-parameter model, a simplified lumped-parameter model and an extended neural-net-based model. The transcendental transfer function of the linearized model is obtained by a Laplace transformation and corresponding initial and boundary conditions. The lumped-parameter model is obtained by a Taylor series extension of the transencdental transfer function. Based on the experience of linear models the structure of the neural net model, as an addendum to the nonlinear distributed-parameter model, is obtained. All four models are tested on a real pipeline data with an artificially generated leak.     

Modeling,simulation and validation of material flow on conveyor belts

In this paper a model comparison approach based on material flow systems is investigated that is divided into a microscopic and a macroscopic model scale. On the microscopic model scale particles are simulated using a model based on Newton dynamics borrowed from the engineering literature. Phenomenological observations lead to a hyperbolic partial differential equation on the macroscopic model scale. Suitable numerical algorithms are presented and both models are compared numerically and validated against real-data test settings.     

VLES turbulence model for an Eulerian–Lagrangian modeling concept for bubble plumes

Traditional Reynolds-averaged Navier–Stokes (RANS) approaches to turbulence modeling, such as the k-ϵ model, have some well-known shortcomings when modeling transient flow phenomena. To mitigate this, a filtered URANS model has been derived where turbulent structures larger than a given filter size (typically grid size) is captured by the flow equations and smaller structures are modeled according to a modified k-ϵ model. This modeling approach is also known as a VLES model (Very Large Eddy Scale model), and provides more details of the transient turbulence than the k-ϵ model at little extra computational cost.In this study a two-phase extension to the VLES model is described. A modeling concept for bubble plumes has been developed in which the bubbles are tracked as particles and the flow of liquid is solved by the Navier–Stokes equations in a traditional mesh based approach. The flow of bubbles and liquid is coupled in an Eulerian–Lagrangian model. Turbulent dispersion of the bubbles is treated by a random walk model. The random walk model depends on an estimation of the eddy life time. The eddy life time for the VLES model differs from a k-ϵ model, and its mathematical expression is derived.The model is applied to ocean plumes emanating from discharge of gas at the ocean floor. Validation with experiments and comparison with k-ϵ model are shown.     

The Closeness of the τ-Standard Part of a Set

In this paper,the closeness of the τ-standard part of a set is discussed.Some related propositions of the τ-neighborhood system of a set are given.And then some related conclusions of the τ-monad of a set and the τ-standard part of a set are presented.And based on it,the necessary and sufficient conditions of the enlarged model and the saturated model are showed.Finally,some sufficient conditions that the τ-standard part of a set is closed are proved in the enlarged model and the saturated model.     

部分线性变系数模型Backfitting估计的渐近性质

作为部分线性模型与变系数模型的推广,部分线性变系数模型是一类应用广泛的数据分析模型.利用Backfitting方法拟合这类特殊的可加模型,可得到模型中常值系数估计量的精确解析表达式,该估计量被证明是n~(1/2)相合的.最后通过数值模拟考察了所提估计方法的有效性.     

Modelling systems with renewable resources based on functional operators with shift

A method for the study of systems with renewable resources is proposed. The individual and the group parameters are separated and a discretization of time is carried out. We obtain equilibrium proportions which are functional equations with shift. A cyclic model and an open model are considered. Conditions for the existence and uniqueness of the solution are formulated for the cyclic model. For the open model, the system’s evolution is analyzed.     

基于跳扩散过程的Omega模型

文章通过在Omega模型中加入布朗运动扰动项,提出了一种跳扩散Omega破产模型.在索赔额为指数分布的情形下,给出了破产率函数是常数时的破产概率函数表达式.文章进一步研究了破产概率和盈余过程的“负占有时”之间的关系,并给出了破产概率函数的第二种推导过程.最后通过两个数值试验,将我们的模型与Albreeher和Lautscham (2013)的Omega模型的破产概率进行了比较分析.     

Multi-parameter Tikhonov regularization and model function approach to the damped Morozov principle for choosing regularization parameters

In this paper, we study the multi-parameter Tikhonov regularization method which adds multiple different penalties to exhibit multi-scale features of the solution. An optimal error bound of the regularization solution is obtained by a priori choice of multiple regularization parameters. Some theoretical results of the regularization solution about the dependence on regularization parameters are presented. Then, an a posteriori parameter choice, i.e., the damped Morozov discrepancy principle, is introduced to determine multiple regularization parameters. Five model functions, i.e., two hyperbolic model functions, a linear model function, an exponential model function and a logarithmic model function, are proposed to solve the damped Morozov discrepancy principle. Furthermore, four efficient model function algorithms are developed for finding reasonable multiple regularization parameters, and their convergence properties are also studied. Numerical results of several examples show that the damped discrepancy principle is competitive with the standard one, and the model function algorithms are efficient for choosing regularization parameters.     

Identification of Non-Varying Coefficients in Varying- Coefficient Models

A partially varying-coefficient model is one of the useful modelling tools. In this model, some coefficients of a linear model are kept to be constant whilst the others are allowed to vary with another factor. However, rarely can the analysts know a priori which coefficients can be assumed to be constant and which ones are varying with the given factor. Therefore, the identification problem of the constant coefficients should be solved before the partially varying-coefficient model is used to analyze a real-world data set. In this article, a simple test method is proposed to achieve this task, in which the test statistic is constructed as the sample variance of the estimates of each coefficient function in a well-known varying-coefficient model. Moreover two procedures, called F-approximation and three-moment X~2 approximation, are employed to derive the p-value of the test. Furthermore, some simulations are conducted to examine the performance of the test and the results are satisfactory.