基于随机模糊投资乘数的离散CPPI资产配置研究

以传统CPPI投资策略的分析框架为基础,在风险资产为连续价格波动的条件下,构建离散投资决策时点的CPPI投资策略。引入模糊决策的分析方法度量投资决策者的心理预期,将传统CPPI投资策略中的投资乘数修正为随机模糊投资乘数,采用马尔科夫链蒙特卡洛模拟风险资产未来市场价格,利用模糊隶属函数描述投资决策者对未来市场运行状况预期的不确定性,保证即使投资决策者预期不精确的条件下,也能保证离散CPPI投资策略获得相对稳定的投资效果。利用中国证券市场上的真实数据进行实证检验,认为:随机模糊投资乘数最大限度地涵盖了投资决策者主观预测的不确定性;基于随机模糊投资乘数的离散CPPI投资策略在不同的市场运行状况中,较传统的CPPI投资策略更具投资的灵活性,可以在保证投资保险的前提下,追求较高的投资收益。     

带有控制输入扰动和死区的混沌系统自适应模糊控制

针对带有非线性输入和控制增益矩阵扰动的未知时变时滞混沌系统,提出了一种自适应模糊变结构控制方法.设计的控制器可以保证跟踪误差收敛到原点的可调邻域内,并且闭环系统所有信号有界.该方法对系统扰动的变化能保持较好的鲁棒性.最后以多卷波混沌系统为例的仿真实验进一步验证了该方法的有效性.     

支持向量机回归在电子器件易损性评估中的应用

针对现有的以概率统计理论为基础的方法和模糊神经网络法必须建立在大量统计数据基础之上,以及模糊信息扩散估计法可能对器件失效阈值估计过高的问题,提出将模糊信息处理技术用于对原始实验数据的处理,得到训练样本,在此基础上利用支持向量机回归预测一定功率的高功率微波辐照条件下电子器件的损伤概率。仿真结果表明:该方法与模糊神经网络法都较好地给出了预测结果,但该方法具有更高的精度（均方根误差为7.40610-5）,并且克服了在样本数据减半的小样本情况下模糊神经网络法可能出现野值的缺陷。     

模糊自整定比例积分控制在空间三维纳米定位台的应用

介绍了一种空间三自由度纳米定位平台,其应用背景为光刻投影物镜波像差检测系统的精密对准,因此对定位精度和定位速度都提出了很高的要求。首先简要介绍了空间三维纳米定位台;然后将模糊控制同传统PI(比例积分)控制相结合,利用定位偏差和偏差变化率信息,通过模糊推理实时调整PI控制参数,并在VC++环境下实现了模糊自整定PI参数的控制算法。实验结果表明,该控制方法较常规PI控制器能够有效地提高响应速度,减小阶跃响应超调量,保证了控制的实时性。     

A new method for solving linear multi-objective transportation problems with fuzzy parameters

There are several methods in the literature for solving transportation problems by representing the parameters as normal fuzzy numbers. Chiang [J. Chiang, The optimal solution of the transportation problem with fuzzy demand and fuzzy product, J. Inform. Sci. Eng. 21 (2005) 439-451] pointed out that it is better to represent the parameters as (λ, ρ) interval-valued fuzzy numbers instead of normal fuzzy numbers and proposed a method to find the optimal solution of single objective transportation problems by representing the availability and demand as (λ, ρ) interval-valued fuzzy numbers. In this paper, the shortcomings of the existing method are pointed out and to overcome these shortcomings, a new method is proposed to find solution of a linear multi-objective transportation problem by representing all the parameters as (λ, ρ) interval-valued fuzzy numbers. To illustrate the proposed method a numerical example is solved. The advantages of the proposed method over existing method are also discussed.     

Some ideas to minimize an empirically given fuzzy function

In real world problems, usually, the response variable as well as the adjustable control variables are subject to vagueness and uncertainty. These properties can be taken into account by means of specifying fuzzy sets for the respective values. In the paper the case is considered that the function to be minimized is a fuzzy one and can only be inspected point by point. Then a region is to be found where the values of the response variables are minimum in a given sense. Hence a sequential procedure is sketched for which the observed values will run into such a region.     

模糊集范畴及集合范畴上的模

本文构造了在完备格上模糊集范畴.利用极小扩展原则和范畴的性质,获得了函子Uα构成集合范畴上的模结构,推广了P.Eklund的结论.     

Mehar’s method for solving fuzzy sensitivity analysis problems with LR flat fuzzy numbers

In published works on fuzzy linear programming there are only few papers dealing with stability or sensitivity analysis in fuzzy mathematical programming. To the best of our knowledge, till now there is no method in the literature to deal with the sensitivity analysis of such fuzzy linear programming problems in which all the parameters are represented by LR flat fuzzy numbers. In this paper, a new method, named as Mehar’s method, is proposed for the same. To show the advantages of proposed method over existing methods, some fuzzy sensitivity analysis problems which may or may not be solved by the existing methods are solved by using the proposed method.     

Type-2 T–S fuzzy impulsive control of nonlinear systems

A novel impulsive control approach based on interval Type-2 T–S fuzzy model has been presented for nonlinear systems in this paper. This approach makes up for the drawback of Type-1 fuzzy impulsive control, which cannot fully handle the uncertainties in describing the complex nonlinear systems by Type-1 fuzzy membership functions and cannot give rigorous fuzzy rules. Further more, this approach uses the “broad band” effect of the Type-2 membership functions to solve the noise of training data and exterior disturbance of the Type-1 fuzzy impulsive control. By using Lyapunov theory and Lipschitz condition, which is combined with integrated approaches such as comparison methods and linear matrix inequalities, the Type-2 fuzzy impulsive controller is designed and the general asymptotical stability analysis of the systems is given. Finally, the simulation of the inverted pendulum model demonstrates the validity and superiority of the proposed method by easily determining the membership functions and choosing minimum number of fuzzy rules and the method can handle random disturbance and data uncertainties very well.