In comparison to fuzzy sets, intuitionistic sets are much more efficient at representing and processing uncertainty. Distance measures quantify how the information conveyed by differs from one another. Researchers have suggested many distance assess difference between but several of them produce contradictory results in practice violate fundamental axioms measure. this article, we introduce a n...

Abstract Picture fuzzy set (PFS) is a direct generalization of the sets (FSs) and intuitionistic (IFSs). The concept PFS suitable to model situations that involve more answers type yes, no, abstain, refuse. In this study, we introduce novel picture (PF) distance measure on basis operation functions membership, non-membership, neutrality, refusal, upper bound function membership two PFSs. We con...

In the present paper, Characteristics of fuzzy project network using statistical data are discussed in detail in order to calculate the fuzzy critical path, fuzzy earliest times, fuzzy latest times and fuzzy total float. Fuzzy number as fuzzy activity time is constructed using interval estimate by calculating mean, variance and standard error. A new ranking function is used to discriminate the ...

Spectral clustering has been successfully used in the field of pattern recognition and image processing. The efficiency of spectral clustering, however, depends heavily on the similarity measure adopted. A widely used similarity measure is the Gaussian kernel function where Euclidean distance is used. Unfortunately, the Gaussian kernel function is parameter sensitive and the Euclidean distance ...

the paper analyses issues leading to errors in graphic object classifiers. thedistance measures suggested in literature and used as a basis in traditional, fuzzy, andneuro-fuzzy classifiers are found to be not suitable for classification of non-stylized orfuzzy objects in which the features of classes are much more difficult to recognize becauseof significant uncertainties in their location and...

Different clustering algorithms are based on different similarity or distance measures (e.g. Euclidian distance, Minkowsky distance, Jackard coefficient, etc.). Jarvis-Patrick clustering method utilizes the number of the common neighbors of the k-nearest neighbors of objects to disclose the clusters. The main drawback of this algorithm is that its parameters determine a too crisp cutting criter...

This paper presents a new method for similarity measures between intuitionistic fuzzy sets (IFSs). We will present a method to calculate the distance between IFSs on the basis of the Hausdorff distance. We will then use this distance to generate a new similarity measure to calculate the degree of similarity between IFSs. Finally we will prove some properties of the proposed similarity measure a...

Due to advances in hardware performance, user-friendly interfaces are becoming one of the major concerns in information systems. Linguistic conversation is a very natural way of human communications. Fuzzy techniques have been employed to liaison the discrepancy between the qualitative linguistic terms and quantitative computerized data. This paper deals with linguistic queries using clustering...

In this article we apply a new measure of similarity to analyse the extent of agreement in a group of experts. The proposed measure takes into account not only a pure distance between intuitionistic fuzzy preferences but also examines if the compared preferences are more similar or more dissimilar. The agreement of a whole group is assessed via an aggregation of individual testimonies expressed...