Joint distributions of random sets and their relation to copulas

Random sets are set-valued random variables. They have been applied in various fields like stochastic geometry, statistics, economics, engineering or computer science, and are often used for modeling uncertainty. In an earlier paper the author has defined joint capacity and joint containment functionals which are multivariate set functions describing the joint distribution of random sets. This paper is concerned with the question how copulas can be used to describe or model the dependence of random sets. It is demonstrated that a joint containment functional can be related to its margins by a family of copulas. Furthermore, the paper provides a first insight how copulas can be used to define joint containment functionals.     

On independent sets in random graphs

The independence number of a sparse random graph G(n,m) of average degree d = 2m/n is well‐known to be with high probability, with in the limit of large d. Moreover, a trivial greedy algorithm w.h.p. finds an independent set of size , i.e., about half the maximum size. Yet in spite of 30 years of extensive research no efficient algorithm has emerged to produce an independent set with size for any fixed (independent of both d and n). In this paper we prove that the combinatorial structure of the independent set problem in random graphs undergoes a phase transition as the size k of the independent sets passes the point . Roughly speaking, we prove that independent sets of size form an intricately rugged landscape, in which local search algorithms seem to get stuck. We illustrate this phenomenon by providing an exponential lower bound for the Metropolis process, a Markov chain for sampling independent sets. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 436–486, 2015     

关于《线性代数》教材改革的几点想法

随着现代科学技术的迅猛发展,尤其是计算机技术的广泛应用,我们应当在工科数学课程的教学内容、教学方法和教学手段上积极改革,与时俱进,以改进教学方法,提高教学质量,使得工科学生能借助于计算机,学好本专业所需的数学知识.在这篇短文中,我们想就《线性代数》的教学内容的改革     

Numerical approach for generic three-phase flow based on cut-cell and ghost fluid methods

In this paper, we introduce numerical methods that can simulate complex multiphase flows. The finite volume method, applying Cartesian cut-cell is used in the computational domain, containing fluid and solid, to conserve mass and momentum. With this method, flows in and around any geometry can be simulated without complex and time consuming meshing. For the fluid region, which involves liquid and gas, the ghost fluid method is employed to handle the stiffness of the interface discontinuity problem. The interaction between each phase is treated simply by wall function models or jump conditions of pressure, velocity and shear stress at the interface. The sharp interface method “coupled level set (LS) and volume of fluid (VOF)” is used to represent the interface between the two fluid phases. This approach will combine some advantages of both interface tracking/capturing methods, such as the excellent mass conservation from the VOF method and good accuracy of interface normal computation from the LS function. The first coupled LS and VOF will be generated to reconstruct the interface between solid and the other materials. The second will represent the interface between liquid and gas.     

A discontinuous Galerkin immersed boundary solver for compressible flows: Adaptive local time stepping for artificial viscosity–based shock-capturing on cut cells

We present a higher-order cut cell immersed boundary method (IBM) for the simulation of high Mach number flows. As a novelty on a cut cell grid, we evaluate an adaptive local time stepping (LTS) scheme in combination with an artificial viscosity–based shock-capturing approach. The cut cell grid is optimized by a nonintrusive cell agglomeration strategy in order to avoid problems with small or ill-shaped cut cells. Our approach is based on a discontinuous Galerkin discretization of the compressible Euler equations, where the immersed boundary is implicitly defined by the zero isocontour of a level set function. In flow configurations with high Mach numbers, a numerical shock-capturing mechanism is crucial in order to prevent unphysical oscillations of the polynomial approximation in the vicinity of shocks. We achieve this by means of a viscous smoothing where the artificial viscosity follows from a modal decay sensor that has been adapted to the IBM. The problem of the severe time step restriction caused by the additional second-order diffusive term and small nonagglomerated cut cells is addressed by using an adaptive LTS algorithm. The robustness, stability, and accuracy of our approach are verified for several common test cases. Moreover, the results show that our approach lowers the computational costs drastically, especially for unsteady IBM problems with complex geometries.     

基于粗糙集模糊神经网络的爆破振动危害预测

为了探索一种能克服单因素预测的局限性、提高爆破振动危害预测精度的方法,基于粗糙集模糊神经网络理论,建立了综合考虑爆破振动幅值、主频率、主频率持续时间及结构动力特性等10个因素的民房破坏程度预测模型;用铜绿山矿爆破振动和民房破坏情况观测数据,对该模型进行了训练和测试,测试结果与现场观测结果具有良好的一致性。研究表明:粗糙集理论可将现场数据进行属性约简,简化输入变量,缩小神经网络的搜索空间,改善爆破振动的预测性能;基于粗糙集模糊神经网络理论的爆破振动危害预测模型,能更好地考虑各种因素对危害程度的综合影响,避免了单因素预测的局限性。     

时一空守恒元解元（CE／SE）方法综述

时一空守恒元解元方法是近年来兴起的一种全新的高分辨率守恒型方程计算方法．它具有物理概念清晰、计算精度高和格式构造简单等优点,是一种具有广阔发展前景的计算方法．本文详细地介绍了cE／ss方法的基本原理、发展历史、应用情况和最新进展、并指出了当前研究的不足和发展方向．     

基于概率语言术语集的服务外包风险评估方法

考虑服务外包风险评估的不确定性,采用概率语言术语集获取FMEA方法所需的专家评价信息,通过给语言集赋予不同的概率以表达偏好的程度。针对传统FMEA方法没有考虑风险间的相互影响关系,风险严重度评估不够准确的问题,采用广义Choquet积分分析风险间的相互影响关系,得到修正后的风险严重度。考虑严重度、发生度和难检度直接相乘准确性低的问题,采用概率语言VIKOR方法对风险的三个因子进行综合评估。最后以公共体育场馆服务外包风险评估为例,验证了所提方法的有效性。     

直觉L模糊子群的刻画

本文研究了一个群G上的直觉L模糊子群.借助于L模糊集的截集,反模糊子群,得到了群G上的直觉L模糊子群的等价刻画.在直觉L模糊子群和群G上的子群族之间可以建立起一一对应.