This paper introduces fuzzy belief nets (FBN). The ability to invert arcs between nodes is key to solving belief nets. The inversion is accomplished by defining closeness measures which allow diagnostic reasoning from observed symptoms to cause of failures. The closeness measures are motivated by a Lukasiewicz operator which takes into account the distance from an observed symptom set to the mo...

Fuzzy Hamming Distance is successfully used in a Content-Based Image Retrieval (CBIR) system as a similarity measure. The system performs a m × n partitioning of the compared images and for each partitions pairs evaluates FHD. In the last step the FHD are defuzzified and the results are combined in a final score. In order to take full advantage of the use of fuzzy sets, the current study invest...

In this paper, a novel modified evolutionary fuzzy clustering has been proposed. This technique exploits parameters such as Minkowski distance, Xie Beni index, and classification entropy. These parameters turn to account to polish the performance measure by incorporating shape of the cluster, class compactness and partitioning quality respectively in standard Fuzzy C-Means clustering. Moreover,...

In this paper we introduce a new approach for adjustment of membership functions, generation, and reduction of fuzzy rule base from data in the same time. The proposed approach consists of five steps: First, generate fuzzy rules from data using Mendel & Wang Method introduced in [1]. Second, calculate the degree of similarity between rules. Third, measure the distance between the numerical valu...

In this paper, we axiomatically introduce fuzzy multi-measures on bounded lattices. In particular, we make a distinction between four different types of fuzzy set multi-measures on a universe X, considering both the usual or inverse real number ordering of this lattice and increasing or decreasing monotonicity with respect to the number of arguments. We provide results from which we can derive ...

Using the notion of a fuzzy point and its belongness to and quasicoincidence with a fuzzy subset, some new concepts of a fuzzy interior ideal in Abel Grassmann’s groupoids S are introduced and their interrelations and related properties are invesitigated. We also introduce the notion of a strongly belongness and strongly quasicoincidence of a fuzzy point with a fuzzy subset and characterize fuz...

In this paper, we extend the distance measure to the linguistic fuzzy sets, and develop the linguistic distance operators, such as linguistic weighted distance (LWD) operator, linguistic ordered weighted distance (LOWD) operator, and study some of their desired properties. These aggregation operators are very useful for decision-making problems because they establish a comparison between an ide...

Record linkage is a well known technique used to link records from one database to records from another database which make reference to the same individuals. Although it is usually used in database integration, it is also used in the data privacy field for the disclosure risk evaluation of protected datasets. In this paper we compare two different supervised algorithms which rely on distance-b...

While focusing on document clustering, this work presents a fuzzy semi-supervised clustering algorithm called fuzzy semi-Kmeans. The fuzzy semi-Kmeans is an extension of K-means clustering model, and it is inspired by an EM algorithm and a Gaussian mixture model. Additionally, the fuzzy semi-Kmeans provides the flexibility to employ different fuzzy membership functions to measure the distance b...

The hesitant fuzzy soft set (HFSS), as a combination of hesitant fuzzy and soft sets, is regarded as a useful tool for dealing with the uncertainty and ambiguity of real-world problems. In HFSSs, each element is defined in terms of several parameters with arbitrary membership degrees. In addition, distance and similarity measures are considered as the important tools in different areas such as ...