Value sharing of meromorphic functions and their derivatives

In this paper, we estimate the size of ρn's in the famous L. Zalcman's lemma. With it, we obtain some uniqueness theorems for meromorphic functions f and f^′ when they share two transcendental meromorphic functions.     

Two normality criteria and the converse of the Bloch principle

We prove two normality criteria for a family of meromorphic functions satisfying a certain differential condition and provide a counterexample to the converse of the Bloch principle.     

模糊数和模糊值函数的等式限定运算

通过模糊数的结构元表示方法,利用两个单调函数的自反单调变换构造了等式限定算子,推广了文[6]中的等式限定运算,处理了存在负模糊情况下关于乘法运算的不可逆问题.同时,本文还将等式限定运算推广到模糊值函数上,提出了模糊值函数等式限定运算的结构元方法,解决了模糊值函数运算的不可逆问题.     

Fuzzy区间值函数的含参量积分及一致收敛性

在一元实函数无穷积分定义的基础上,定义了含参量Fuzzy区间值函数的正常积分和无穷积分,给出了含参量无穷积分一致收敛的定义和判定定理.     

区间值模糊数与区间值粗糙模糊数

把经典Z.Pawlak粗糙集与区间值模糊集相结合,研究区间值模糊数的基本理论.讨论区间值模糊数的基本性质和四则运算法则及其与其它各种区间数的关系,并给出区间值模糊数的刻画定理.同时,在经典Z.Pawlak粗糙集的框架下定义实直线上的粗闭区间套,提出区间值粗糙模糊数的定义.利用模糊数的表现定理给出区间值粗糙模糊数的一个刻画.     

Bayesian Copulae Distributions, with Application to Operational Risk Management

The aim of this paper is to introduce a new methodology for operational risk management, based on Bayesian copulae. One of the main problems related to operational risk management is understanding the complex dependence structure of the associated variables. In order to model this structure in a flexible way, we construct a method based on copulae. This allows us to split the joint multivariate probability distribution of a random vector of losses into individual components characterized by univariate marginals. Thus, copula functions embody all the information about the correlation between variables and provide a useful technique for modelling the dependency of a high number of marginals. Another important problem in operational risk modelling is the lack of loss data. This suggests the use of Bayesian models, computed via simulation methods and, in particular, Markov chain Monte Carlo. We propose a new methodology for modelling operational risk and for estimating the required capital. This methodology combines the use of copulae and Bayesian models.      

Realtime control of robots with initial value perturbations via nonlinear programming methods

The mathematical model of an industrial robot with initial value perturbations is considered as a parametric nonlinear control problem subject to control and state constraints. Based on recent stability results for parametric control problems, a robust nonlinear programming method is proposed for computing the sensitivity derivatives of optimal solutions. Real-time control approximations of perturbed optimal solutions are obtained by evaluating a first order Taylor expansion of the perturbed solution. The efficiency of the real-time approximation is demonstrated for the robot model     

2-型模糊环境下的能源系统优化

基于模糊可能性理论,建立2-型模糊环境下的能源分配优化模型,其中各种类型能源的成本用2-型模糊变量刻画.用均值简约方法简约2-型模糊成本,建立广义期望值意义下的模糊能源分配优化模型.当成本用相互独立的三角2-型模糊变量刻画时,所建立的模糊能源分配优化模型可以转化为等价的参数线性规划.最后提供一个数值例子表明建模思想.     

基于Skewed-t分布的FIGARCH模型与VaR的度量

金融资产收益率序列的波动具有典型的尖峰厚尾和非对称性特征,描述这种特性需以合适的概率分布函数为基础.因此,寻求更好的概率分布函数对风险度量、VaR的计算有着十分重要的意义.有鉴于此引入Skewed-t分布度量VaR,并比较分析了RiskMetrics及FIGARCH类模型度量VaR值的准确程度,本文同时分析了多头头寸和空头头寸情况下的VaR.结果表明,在两种头寸情况下,Skewed-t分布在空头和多头情形对资产厚尾特性以及非对称性的拟合效果均要比正态分布好;在两种头寸中不同的置信水平下,FIAGARCH(CHUNG)模型预测的VaR值改进了使用传统模型的精确性,高估或低估风险的程度较轻.