Large Deviation Probabilities for Square-Gaussian Stochastic Processes

We investigate properties of square-Gaussian stochastic processes. These processes are formed by quadratic forms of Gaussian processes or by limits in the mean square of quadratic forms of Gaussian processes. Special classes of these processes are determined and investigated. For processes from these classes estimates of large deviation probability are obtained. These estimates we use to estimate the probability that Gaussian vector-valued process leave some region on some interval of time. We construct asymptotic confidence regions for estimates of covariance functions of vector-valued Gaussian processes. Criterion of hypothesis testing on covariance functions of these processes is constructed.     

Survival probability in one dimension for theA+B→B reaction with hard-core repulsion

We study the effect of hard-core repulsion (known as the bus effect) betweenB particles on the reaction-diffusion systemA+BB in the continuous-time random walk model in one dimension with theA particles stationary. We show rigorously that the survival probability of theA particles is asymptotically bounded asC ₁lim _t{[–logS(t)]/t ^0.5}C ₂, whereC ₁ andC ₂ are constants. We also do simulations to confirm our results.     

目标散布区对导弹目标选择概率影响的仿真模型

当反舰导弹飞近目标散布区时,导弹搜索雷达必须开机搜索目标,导弹根据目标反射信号的几何或能量特性,利用某一算法从被探测到的,包括敌方施放的假目标在内的所有目标中选择某一目标作为导弹的攻击目标.目标散布区的外形和大小对导弹选择真实目标概率的影响是一个尚未得到深入研究的问题.推导了目标散布区对导弹正确选择目标概率的影响函数;在考虑了目标舰及时提供假目标的仿真模型的基础上,给出了七种导引头选择目标的算法及仿真模型.仿真结果表明,目标散布区影响反舰导弹雷达的开机时间,从而影响导引头选择真实目标的概率及其抗电子干扰能力.     

稀疏过程下变破产下限多元相依风险模型的破产概率

研究了稀疏过程下多元相依风险模型在假定变破产下限的破产概率,其中索赔产生时依赖概率ρ的可能性同时产生一次续保,即续保过程是索赔的ρ-稀疏过程.运用鞅方法得到了当破产下限为某些特征函数时破产概率所满足的不等式或破产概率的具体表达式.     

基于评价信息随机化的群体评价方法与应用

针对群体评价中共识集结的相关问题,从仿真的视角讨论了评价信息随机化的群体共识聚合求解方法。首先,面向实数类型的评价信息,将精确性的数据给予一定的宽松性处理,进一步结合正态分布的3σ原则,利用随机模拟的方式集结出带有概率特征的可能性排序;其次,面向区间数类型的评价信息,整合出各子区间发生概率不同的区间数评价信息,在充分随机模拟的情况下,给出了带有优胜概率特征的可能性排序。最后,通过相应的算例进行求解分析,说明了该方法的可行性和有效性。基于群体共识视角,针对实数和区间数两种类型的评价信息,分别进行相应的随机化处理,并为进一步探索区间数的分布形式提供了一种新的研究思路。     

Optimal generation scheduling for constrained multi-area hydrothermal power systems with cascaded reservoirs

The optimization problem in this paper is targeted at large-scale hydrothermal power systems. The thermal part of the system is a multi-area power pool with tie-line constraints, and the hydro part is a set of cascaded hydrostations. The objective is to minimize the operation cost of the thermal subsystem. This is an integer nonlinear optimization process with a large number of variables and constraints. In order to obtain the optimal solution in a reasonable time, we decompose the problem into thermal and hydro subproblems. The coordinator between these subproblems is the system Lagrange multiplier. For the thermal subproblem, in a multi-area power pool, it is necessary to coordinate the area generations for reducing the operation cost without violating tie limits. For the hydro subsystem, network flow concepts are adopted to coordinate water usage over the entire study time span, and the reduced gradient method is used to overcome the linear characteristic of the network flow method in order to obtain the optimal solution. In this study, load forecasting errors and forced outages of generating units are incorporated in system reliability requirements. Three case studies for the proposed method are presented.     

Efficient Solution Concepts and Their Relations in Stochastic Multiobjective Programming

In this work, different concepts of efficient solutions to problems of stochastic multiple-objective programming are analyzed. We center our interest on problems in which some of the objective functions depend on random parameters. The existence of different concepts of efficiency for one single stochastic problem, such as expected-value efficiency, minimum-risk efficiency, etc., raises the question of their quality. Starting from this idea, we establish some relationships between the different concepts. Our study enables us to determine what type of efficient solutions are obtained by each of these concepts.     

Scale Invariance Properties in the Simulated Annealing Algorithm

The Boltzmann distribution used in the steady-state analysis of the simulated annealing algorithm gives rise to several scale invariant properties. Scale invariance is first presented in the context of parallel independent processors and then extended to an abstract form based on lumping states together to form new aggregate states. These lumped or aggregate states possess all of the mathematical characteristics, forms and relationships of states (solutions) in the original problem in both first and second moments. These scale invariance properties therefore permit new ways of relating objective function values, conditional expectation values, stationary probabilities, rates of change of stationary probabilities and conditional variances. Such properties therefore provide potential applications in analysis, statistical inference and optimization. Directions for future research that take advantage of scale invariance are also discussed.     

The connectivity of a graph on uniform points on [0,1]

A random graph G_n(x) is constructed on independent random points U₁,…,U_n distributed uniformly on [0,1]^d, d1, in which two distinct such points are joined by an edge if the l_∞-distance between them is at most some prescribed value 0<x<1. The connectivity distance c_n, the smallest x for which G_n(x) is connected, is shown to satisfy

(1)

For d2, the random graph G_n(x) behaves like a d-dimensional version of the random graphs of Erdös and Rényi, despite the fact that its edges are not independent: c_n/d_n→1, a.s., as n→∞, where d_n is the largest nearest-neighbor link, the smallest x for which G_n(x) has no isolated vertices.     

Nonlinear Deformational Properties of Dispersely Strengthened Materials

A method and an algorithm for determining the effective deformational properties of dispersely strengthened materials with a physically nonlinear matrix and quasi-spheroidal linearly elastic inclusions are elaborated based on the stochastic differential equations of the physically nonlinear theory of elasticity. Their transformation to integral equations and the application of the method of conditional moments reduce the problem to a system of nonlinear algebraic equations, whose solution is constructed by the iteration method. The deformation diagrams as functions of the volume content of inclusions are investigated.