基于依赖型算子的不确定语言多属性群决策法

研究了属性权重以实数形式给出、属性值以不确定语言变量形式给出的多属性群决策问题。基于不确定语言变量的运算法则,给出了一种基于不确定语言变量及其运算法则的新算子：依赖型不确定语言有序加权几何 (dependent uncertain linguistic ordered weighted geometric, DULOWG) 算子。与该类算子相关联的加权向量依赖于被集结的不确定语言变量,并且对错误或有偏见的不确定语言变量赋予较低的权重来减轻不公平性对评价结果的影响。提出了一种基于ULWGM算子和DULOWG算子的不确定语言多属性群决策方法,并进行了实例分析。     

Two-phase TOPSIS of uncertain multi-attribute group decision-making

To solve the uncertain multi-attribute group decisionmaking of unknown attribute weights, three optimal models are built to decide the corresponding ideal solution weights, standard deviation weights and mean deviation weights. The comprehensive attribute weights are gotten through the product of the above three kinds of weights. And each decision maker's weighted decision matrices are also received by using the integrated attribute weights. The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution (TOPSIS) through dealing with the weighted decision matrices. At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker’s closeness degree to every project. Then the vertical TOPSIS method is used to calculate the closeness degree of each project. So these projects can be ranked according to their values of the closeness degree. The process of the method is also given step by step. Finally, a numerical example demonstrates the feasibility and effectiveness of the approach.     

Coordinating pricing and inventory decisions in a bounded production system with uncertain yield

Most inventory researches assume that production level can fluctuate arbitrarily. However, large fluctuation of the production level in many firms may be much costly. This paper addresses the coordinating pricing and inventory control problem in a bounded production system with uncertain yield, in which the production level is constrained between a maximum and minimum level in each period and the price can be adjusted dynamically. We show that the optimal policy is the interval base-stock-list-price policy. Also, we study the impact of the production bounds and uncertainty of the yield on the production system. Numerical experiments are also performed to study the impact of parameters on the system.     

不确定奇异系统的Terminal滑模控制

针对一类不确定奇异系统,研究其Terminal滑模控制问题。通过非奇异线性变换把不确定奇异系统变换成受限等价形式,利用Lyapunov函数方法,首次提出了一种新的Terminal滑模控制策略,给出了特殊的Terminal滑模超曲面,设计了相应的滑模控制器,实现了滑模运动,保证了系统状态变量在有限时间内收敛到平衡点。给出数值算例,说明了方法的有效性。     

Robust H∞ control for neutral stochastic uncertain systems with time-varying delay

The problem of robust H∞ control for uncertain neutral stochastic systems with time-varying delay is discussed. The parameter uncertaintie is assumed to be time varying norm-bounded. First, the stochastic robust stabilization of the stochastic system without disturbance input is investigated by nonlinear matrix inequality method. Then, a full-order stochastic dynamic output feedback controller is designed by solving a bilinear matrix inequality (BMI), which ensures a prescribed stochastic robust H∞ performance level for the resulting closed loop system with nonzero disturbance input and for all admissible uncertainties. An illustrative example is provided to show the feasibility of the controller and the potential of the proposed technique.     

时变时滞不确定离散奇异切换系统的鲁棒H_∞滤波

研究了含参数不确定的时变时滞离散奇异切换系统的鲁棒H∞滤波问题。利用受限系统等价变换和引进新状态变量,将所讨论的奇异滤波误差系统等价转换为时滞离散标准切换系统。然后构建了一个新颖的Lya-punov—Krasovskii函数。通过对转换后的系统进行讨论,采用线性矩阵不等式形式得到了判定系统正则、因果和一致渐近稳定的充分条件,以及对所允许的不确定性满足H∞性能的滤波器设计方法。所得到的结果具有较小的保守性。最后,通过数值算例验证了本文方法的有效性。     

区间数密度算子及其应用

针对决策信息为区间数形式的不确定多属性决策问题,将密度中间算子由精确值形式拓展到区间数形式.通过引入"区间隶属度"的概念对区间数进行聚类,并给出一种通过规划模型确定密度加权向量的方法;在此基础上,对区间数密度中间算子及其合成算子进行了界定.最后,通过一个算例对区间数密度算子的应用进行了说明.该方法结合区间数的特征,进一步拓展了密度算子的理论体系和实际应用范围.     

基于离群因子的不确定数据生成算法

基于不确定数据的表示模型, 针对属性级不确定数据, 提出一种不确定数据生成算法AC UDGen（attribute level continuous uncertain data set generation algorithm）. 该算法通过引入离群点检测 LOF（local outlier factor）算法, 用每个数据对象的离群因子作为参数来控制不确定数据对象的扰动范围, 可很好地满足原始数据的分布特征, 解决了目前工作中缺乏原始数据分布特征的问题. 实验结果表明, 该算法生成的不确定数据集具有更好的聚类效果, 并降低了离群点对聚类结果的影响, 使每个数据对象MBR(minimum bounding rectangle)的大小可根据自身的分布特征自适应地变化.     

基于D-S证据理论的不确定数据清洗

数据清洗的任务是检测数据中存在的错误、缺失或不一致,通过删除、填充、修改等方法提高数据质量.针对存在元组级不确定性的数据表上的选择投影连接操作,基于D-S证据理论中置信区间的概念,给出辨识框架构建和置信区间计算的方法,提出了一种基于待测数据项置信区间来检测查询结果中错误数据的方法.实验结果表明,提出的不确定数据错误检测方法具有高效性、准确性和可用性.     

剖析三种非经典逻辑的思想来源与特征

论述了概率逻辑,模糊逻辑和不确定逻辑的思想来源;揭示了它们的思想本质特性;比较分析了它们的长处和不足.