面向不确定需求租户集的云服务智能匹配模型

为了解决云计算环境下由海量租户集和资源集间的不确定性因素引起的高质量云服务获取困难的问题,提出了一种描述动态异构租户集不确定性需求的方法.在此基础上,构建属性权重完全未知情况下的云服务智能匹配模型,排除了租户提交权值造成的偏差.神经网络以属性区间计算的相离度作为输入,服务满意度为输出来动态模拟租户集的不确定需求,运用萤火虫算法求解模型获取最优服务组合.最后,实例验证了神经网络的可靠性以及算法的有效性.实验结果表明,模型能有效获取高质量的云服务组合,优于传统的匹配方法.     

用不确定德尔菲法预测GDP

德尔菲法是一种建立在专家意见基础上的预测评估方法.不确定统计是利用不确定理论收集和整理分析专家数据的一种统计方法,其中关键的一点是如何构造不确定变量的不确定分布.把德尔菲法和不确定统计相结合,就得到了一种估计不确定分布的新方法——不确定德尔菲法.对该方法的估计误差进行了改进,得到了一种预测GDP的新方法,并利用其预测邯郸市的生产总值(GDP).     

NONLINEAR EXPECTATIONS AND NONLINEAR MARKOV CHAINS

§1.IntroductionLet(?,F)be a measurable space and let Lb(F)be the space of F-measurable andbounded real functions.A nonlinear expectation is a continuous functionalE[·]:Lb(F)?→Rthat is order preserving(i.e.,E[X1]≥E[X2],if X1≥X2)and constant preserving     

On the worst conditional expectation

We study continuous coherent risk measures on L^p, in particular, the worst conditional expectations. We show some representation theorems for them, extending the results of Artzner, Delbaen, Eber, Heath, and Kusuoka.     

一个矩阵不等式和Bayes无偏估计（英）

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Model conversions of uncertain linear system using the improved block-pulse function approach

This paper presents an improved block-pulse function approach to convert a continuous-time (respectively, discrete-time) structured uncertain linear system into an equivalent discrete-time (respectively, continuous-time) structured uncertain linear model. The concept of the principle of equivalent areas is utilized for the uncertain model conversions. This allows the use of well-established theorems and algorithms in the discrete-time (respectively, continuous-time) domain to indirectly solve the continuous-time (respectively, discrete-time) domain problems. A numerical example is given to demonstrate the effectiveness of the proposed method.     

Robust stabilization for a class of uncertain dynamical systems with time delay

In this paper, a new and simple approach whereby we derive several sufficient conditions on robust stabilizability for a class of uncertain dynamical systems with time delay is presented. Some analytical methods and the Bellman-Gronwall inequality are employed to investigate these sufficient conditions. The notable features of the results obtained are their simplicity in testing the stability of uncertain dynamical systems with time delay and their clarity in giving insight into system analysis. Finally, several numerical examples are given to demonstrate the utilization of the results.The authors would like to acknowledge the many helpful comments provided by the reviewer. Particularly, in the light of these comments, the proof of Theorem 3.1 has been considerably shortened.     

Uncertain input data problems and the worst scenario method

An introduction to the worst scenario method is given. We start with an example and a general abstract scheme. An analysis of the method both on the continuous and approximate levels is discussed. We show a possible incorporation of the method into the fuzzy set theory. Finally, we present a survey of applications published during the last decade. This work was supported by grant 201/04/1503 from the Czech Science Foundation and by the Academy of Sciences of the Czech Republic, Institutional Research Plan No. AV0Z10190503     

不确定关联时滞大系统的自适应分散镇定控制

针对时变的满足一定匹配条件的不确定关联时滞大系统,利用自适应界化技术,给出了设计分散镇定控制器的自适应的方法.其特点是在假设中系统不确定项是有界的,但界是未知的,且在关联项存在时变时滞的情况下证明了闭环自适应系统的渐近稳定性.最后举例说明了该方法的有效性.     

连续随机变量的随机独立性与回归独立性

回归独立性是指给定随机变量 X时 ,随机变量 Y的条件期望 E( Y|X)不依赖于 X.前人讨论了离散型随机变量回归独立性与随机独立性的关系 ,得到了二者等价的充分必要条件 .对连续型随机变量的情形加以讨论 ,获到了二者等价的几个充分必要条件 ,并说明在统计分析中的应用 .