软直觉模糊集

直觉模糊集是在模糊集上增加了一个新的属性参数：非隶属度函数,成为描述“非此非彼”的“模糊概念”的工具。为了提高决策的精确性,将软集与直觉模糊集相结合,构造了一种新的数学模型,即直觉模糊软集,对其性质进行了一些讨论。     

软集参数约简的新方法

软集理论是一种新的处理不确定性问题的数学工具. 讨论了软集与信息系统之间的关系, 介绍了由软集诱导的二元关系, 借助信息系统的属性约简来研究软集的参数约简, 得到了软集参数约简的新方法, 并通过算例验证了方法的有效性.

     

Type‐Reduction of General Type‐2 Fuzzy Sets: The Type‐1 OWA Approach

For general type‐2 fuzzy sets, the defuzzification process is very complex and the exhaustive direct method of implementing type‐reduction is computationally expensive and turns out to be impractical. This has inevitably hindered the development of type‐2 fuzzy inferencing systems in real‐world applications. The present situation will not be expected to change, unless an efficient and fast method of deffuzzifying general type‐2 fuzzy sets emerges. Type‐1 ordered weighted averaging (OWA) operators have been proposed to aggregate expert uncertain knowledge expressed by type‐1 fuzzy sets in decision making. In particular, the recently developed alpha‐level approach to type‐1 OWA operations has proven to be an effective tool for aggregating uncertain information with uncertain weights in real‐time applications because its complexity is of linear order. In this paper, we prove that the mathematical representation of the type‐reduced set (TRS) of a general type‐2 fuzzy set is equivalent to that of a special case of type‐1 OWA operator. This relationship opens up a new way of performing type reduction of general type‐2 fuzzy sets, allowing the use of the alpha‐level approach to type‐1 OWA operations to compute the TRS of a general type‐2 fuzzy set. As a result, a fast and efficient method of computing the centroid of general type‐2 fuzzy sets is realized. The experimental results presented here illustrate the effectiveness of this method in conducting type reduction of different general type‐2 fuzzy sets.     

多粒化模糊软粗糙集模型

为了扩大粗糙集理论的应用,特别是在模糊环境中的应用,基于模糊软集和模糊蕴涵算子,主要研究基于软模糊近似空间的乐观多粒化模糊软粗糙集模型。该模型将参数集根据客户的不同要求或目标进行重组,只选择若干相关参数集参与计算上、下近似,这样定义的上、下近似不再由整个属性集决定,而是根据重组后的多个属性集一并生成,从而使结果更加符合实际需求。另外,还定义了乐观多粒化模糊软粗糙集模型的截集并讨论了其相关性质。最后给出了算例。     

犹豫模糊软集

犹豫模糊集是对模糊集的一种推广,它是一类关于域中每个元素所含隶属度的集合,常应用于群决策中,但由于其本身在参数工具上的缺乏使得难于处理不确定数据。为了提高决策的精确性,将软集与犹豫模糊集结合起来,提出犹豫模糊软集的概念,并给出犹豫模糊软集的基本运算法则和性质。     

Soft sets and soft rough sets

In this study, we establish an interesting connection between two mathematical approaches to vagueness: rough sets and soft sets. Soft set theory is utilized, for the first time, to generalize Pawlak’s rough set model. Based on the novel granulation structures called soft approximation spaces, soft rough approximations and soft rough sets are introduced. Basic properties of soft rough approximations are presented and supported by some illustrative examples. We also define new types of soft sets such as full soft sets, intersection complete soft sets and partition soft sets. The notion of soft rough equal relations is proposed and related properties are examined. We also show that Pawlak’s rough set model can be viewed as a special case of the soft rough sets, and these two notions will coincide provided that the underlying soft set in the soft approximation space is a partition soft set. Moreover, an example containing a comparative analysis between rough sets and soft rough sets is given.     

Algebraic Structures of Rough Sets in Representative Approximation Spaces

In this paper a generalized notion of an approximation space is considered. By an approximation space we mean an ordered pair (U, ), where U is a finite nonempty set and is a covering of U. According to connections between rough sets and concepts we define two types of approximation operations. Hence we obtain two families of rough sets. We show that these families form lattices in special types of representative approximation spaces. The operations on rough sets defined in the above lattices are analogous to classical operations on sets.     

Minkowski‐type distance measures for generalized orthopair fuzzy sets

The generalized orthopair fuzzy set inherits the virtues of intuitionistic fuzzy set and Pythagorean fuzzy set in relaxing the restriction on the support for and support against. The very lax requirement provides decision makers great freedom in expressing their beliefs about membership grades, which makes generalized orthopair fuzzy sets having a wide scope of application in practice. In this paper, we present the Minkowski‐type distance measures, including Hamming, Euclidean, and Chebyshev distances, for q‐rung orthopair fuzzy sets. First, we introduce the Minkowski‐type distances of q‐rung orthopair membership grades, based on which we can rank orthopairs. Second, we propose several distances over q‐rung orthopair fuzzy sets on a finite discrete universe and subsequently discuss their applications to multiattribute decision‐making problems. Then we extend these results to a continuous universe, both bounded and unbounded cases are considered. Some illustrative examples are employed to substantiate the conceptual arguments.     

Rough set theory for the interval-valued fuzzy information systems

The notion of a rough set was originally proposed by Pawlak [Z. Pawlak, Rough sets, International Journal of Computer and Information Sciences 11 (5) (1982) 341-356]. Later on, Dubois and Prade [D. Dubois, H. Prade, Rough fuzzy sets and fuzzy rough sets, International Journal of General System 17 (2-3) (1990) 191-209] introduced rough fuzzy sets and fuzzy rough sets as a generalization of rough sets. This paper deals with an interval-valued fuzzy information system by means of integrating the classical Pawlak rough set theory with the interval-valued fuzzy set theory and discusses the basic rough set theory for the interval-valued fuzzy information systems. In this paper we firstly define the rough approximation of an interval-valued fuzzy set on the universe U in the classical Pawlak approximation space and the generalized approximation space respectively, i.e., the space on which the interval-valued rough fuzzy set model is built. Secondly several interesting properties of the approximation operators are examined, and the interrelationships of the interval-valued rough fuzzy set models in the classical Pawlak approximation space and the generalized approximation space are investigated. Thirdly we discuss the attribute reduction of the interval-valued fuzzy information systems. Finally, the methods of the knowledge discovery for the interval-valued fuzzy information systems are presented with an example.     

Reliable controllable sets for constrained Markov‐Jump Linear Systems

Robust λ‐contractive sets have been proposed in previous literature for uncertain polytopic linear systems. It is well known that, if initial state is inside such sets, it is guaranteed to converge to the origin. This work presents the generalization of such concepts to systems whose behaviour changes among different linear models with probability given by a Markov chain. We propose sequence‐dependent sets and associated controllers that can ensure a reliability bound when initial conditions are outside the maximal λ‐contractive set. Such reliability bound will be understood as the probability of actually reaching the origin from a given initial condition without violating constraints. As initial conditions are further away from the origin, the likelihood of reaching the origin decreases. Copyright © 2015 John Wiley & Sons, Ltd.     

Interval‐valued probabilistic linguistic term sets in multi‐criteria group decision making

The theory of probabilistic linguistic term sets (PLTSs) is very useful in objectively dealing with the multi‐criteria group decision making (MCGDM) problems in which there is hesitancy in providing linguistic assessments; and PLTSs allow experts to express their preferences on one linguistic term over another. In order to reflect the uncertainty and inconsistency of decision‐makers and handle incomplete linguistic information, we propose a new PLTS called interval‐valued probabilistic linguistic term set (IVPLTS). In addition, the existing approaches associated with PLTSs are limited or highly complex in real applications. Therefore, new operations, comparison laws, and aggregation operators are developed for IVPLTS. Furthermore, we establish an efficient framework for MCGDM problems based on the proposed comparison method and the fuzzy preference relation. Then we apply it to a real‐life case under linguistic environment. The extended TOPSIS methods combined with PLTSs by using different operational laws are also included for comparison. The final results demonstrate the efficiency and practicality of the new framework.     

Vague软集的模糊熵和它的一些性质

Vague软集理论被认为是一种新的处理不确定信息的数学工具,而模糊熵又是度量各种不确定信息的重要技术.文章基于Vague集思想和软集思想之间的联系,以及Vague集与软集现有理论,在Vague集模糊熵公理化定义的基础上,初步提出了Vague软集的模糊熵的公理化定义.同时给出了一种Vague软集的模糊熵的计算公式,并在此基础上证明了我们的模糊熵公式具有一些良好的数学性质.所得结果扩展了Vague软集理论的研究范围,并提出了该领域未来可研究的方向.     

Possibility neutrosophic soft sets and PNS-decision making method

In this paper, we introduce concept of possibility neutrosophic soft set and define some related concepts such as possibility neutrosophic soft subset, possibility neutrosophic soft null set, and possibility neutrosophic soft universal set. Then, based on definitions of n-norm and n-conorm, we define set theoretical operations of possibility neutrosophic soft sets such as union, intersection and complement, and investigate some properties of these operations. We also introduce AND-product and OR-product operations between two possibility neutrosophic soft sets. We propose a decision making method called possibility neutrosophic soft decision making method (PNS-decision making method) which can be applied to the decision making problems involving uncertainty based on AND-product operation. We finally give a numerical example to display application of the method that can be successfully applied to the problems.     

Soft topology

The concept of soft sets is introduced as a general mathematical tool for dealing with uncertainty. In this work, we define the soft topology on a soft set, and present its related properties. We then present the foundations of the theory of soft topological spaces.     

变精度软粗糙集

从集合间的包含程度出发,构造了一种基于包含度的变精度软粗糙集模型。提出带参数的变精度近似算子的定义,得到了它的基本性质和定理,并给出了证明;定义了双精度软粗糙集的近似算子,研究了其性质;讨论了该模型与其他粗糙集模型的关系以及退化条件;举例说明了在信息处理中的应用。     

Execution models for reconfigurable embedded real‐time systems

This paper deals with the verification and assignment into the execution environment of Reconfigurable Control Applications following the Component‐based International Industrial Standard IEC61499. According to this Standard, a Function Block (FB) is an event‐triggered component and an application is an FB network that has to meet temporal properties according to user requirements. If a reconfiguration scenario is applied at run‐time, then the FB network implementing the application is totally changed or modified. To cover all possible cases, we classify such scenarios into three classes and we define an agent‐based architecture designed with nested state machines to automatically handle all possible reconfigurations. To verify and assign Function Blocks corresponding to each reconfiguration scenario into the execution environment, we define an approach based on the exploration of reachability graphs to verify temporal properties. This approach constructs feasible Operating System tasks encoding the FB network that corresponds to each scenario. Therefore, the application is considered as sets of Operating System (OS) tasks where each set is to load in memory when the corresponding reconfiguration scenario is applied by the agent. We developed the tool X ‐Assign supporting these contributions that we apply on the FESTO production system available in our research laboratory. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Stability and performance analysis of time‐delay LPV systems with brief instability

Linear parameter‐varying (LPV) systems provide a systematic framework for the study of nonlinear systems by considering a representative family of linear time‐invariant systems parameterized by system parameters residing in a compact set. The brief instability concept in such systems allows the linear system to be unstable for some trajectories of the LPV parameter set, so that instability occurs only for short periods of time. In the present paper, we extend the notion of brief instability to LPV systems with time delay in their dynamics. The results provide tools for the stability and performance analysis of such systems, where performance is evaluated in terms of induced ??₂‐gain (or so‐called ??_∞ norm). The main results of this paper illustrate that stability and performance conditions can be evaluated by examining the feasibility of parameterized sets of linear matrix inequalities (LMIs). Using the results of this paper, we then investigate analysis conditions to guarantee the asymptotic stability and ??_∞ performance of fault‐tolerant control (FTC) systems, in which instability may take place for a short period of time due to the false identification of the fault signals provided by a fault detection and isolation (FDI) module. The numerical examples are used to illustrate the qualification of the proposed analysis and synthesis results for addressing brief instability in time‐delay systems. Copyright © 2010 John Wiley & Sons, Ltd.     

ε‐Optimal Value and Approximate Multidimensional Dual Dynamic Programming

This paper develops an approximate dual dynamic programming for an ε? optimal multidimensional control problem governed by first order hyperbolic equations. The problem considered is of the Dieudonne‐Rashevsky type and contains as a particular case class‐qualified deposit and Capital theory problems. It is proven that each Lipschitz continuous function satisfying the dual Hamilton‐Jacobi inequality can be used to define an ε‐optimal value.     

Higher Order Vagueness in Geographical Information: Empirical Geographical Population of Type n Fuzzy Sets

Fuzzy set theory has been suggested as a means for representing vague spatial phenomena, and is widely known for directly addressing some of the issues of vagueness such as the sorites paradox. Higher order vagueness is widely considered a necessary component of any theory of vagueness, but it is not so well known that it too is competently modelled by Type n Fuzzy sets. In this paper we explore the fuzzy representation of higher order vagueness with respect to spatial phenomena. Initially we relate the arguments on philosophical vagueness to Type n Fuzzy sets. As an example, we move on to an empirical generation of spatial Type 2 Fuzzy sets examining the spatial extent of mountain peaks in Scotland. We show that the Type 2 Fuzzy sets can be populated by using alternative parameterisations of a peak detection algorithm. Further ambiguities could also be explored using other parameters of this and other algorithms. We show some novel answers to interrogations of the mountain peaks of Scotland. The conclusion of this work is that higher order vagueness can be populated for Type 2 and higher fuzzy sets. It does not follow that it is always necessary to examine these higher order uncertainties, but a possible advantage in terms of the results of spatial inquiry is demonstrated.