Measurement results contain different kinds of uncertainty. Besides systematic errors andrandom errors individual measurement results are also subject to another type of uncertainty,so-called emph{fuzziness}. It turns out that special fuzzy subsets of the set of real numbers $RR$are useful to model fuzziness of measurement results. These fuzzy subsets $x^*$ are called emph{fuzzy numbers}. The m...

Uncertain set theory is a generalization of uncertainty theory that has become a new branch of mathematics for modeling human belief degrees. Uncertain set is a fundamental concept to describe unsharp concepts in uncertain set theory. The moments are important characteristics of an uncertain set. This paper studies the moments and central moments of uncertain set and gives some formulas to calc...

We consider pattern matching problems where patterns are presented as sequences of fuzzy constraints on input elements. Given an infinite alphabet A, a pattern P [α,β] is a sequence ­ μi1 , μi2 , ..., μim ® of membership functions μij defined on A. The pattern P fuzzy matches an input sequence t ∈ A∗ if t = ux1x2 · · ·xmv such that

Scene classification has received much attention in the recent past. How images can be efficiently classified becomes an important research topic. Most of the stateof-the-art solutions assumed that scene classes are mutually exclusive. But, different human beings have different perceptions, and different people tend to respond inconsistently even to the same scene images. Hence, a scene image m...

A set o f questionnaires was prepared to compare four elicitation methods: point esthnation, bzterval estflnation, membership function exemplification, and pairwise comparison. Technical and nontechnical topics were involved, assuming subjects performed either as measurenlent instruments or as repositories o f knowledge. The advantages, disadvantages, and limitations of each method are discusse...

*Correspondence: [email protected] School of Science, Hebei University of Engineering, Handan 056038, China Abstract Uncertain set is a set-valued function on an uncertainty space, and attempts to model unsharp concepts. Membership function is used to describe the membership degree that a value belongs to the uncertain set. In order to estimate the membership function for an uncertain set via...

It is likely in real-world applications that only little data is available for training a knowledge-based system. We present a method for automatically training the knowledge-representing membership functions of a Fuzzy-Pattern-Classification system that works also when only little data is available and the universal set is described insufficiently. Actually, this paper presents how the Modifie...

Network-centric military operations are redefining information overload as military commanders and staffs are inundated with vast amounts of information. Recent research has developed a fuzzy-based system to assign a Value of Information (VoI) determination for individual pieces of information. This paper presents an investigation on the effect of using triangular and trapezoidal fuzzy membersh...

A fuzzy based method has been proposed for identification of probable capacitor nodes of radial distribution system. Simulated annealing technique has been used for final selection of the capacitor sizes. New fuzzy membership functions have been formulated where the active power membership is an exponential function of the nodal per unit active power and branch active power loss, the reactive m...

Rough set approximations of Pawlak [15] are sometimes generalized by using similarities between objects rather than elementary sets. In practical applications, both knowledge about properties of objects and knowledge of similarity between objects can be incomplete and inconsistent. The aim of this paper is to define set approximations when all sets, and their approximations, as well as similari...