A NOVEL APPROACH TO CHARACTERIZING HESITATIONS IN INTUITIONISTIC FUZZY NUMBERS

Building upon the concept of D α operator introduced by Atanassov (1989), this article proposes an improved objective approach and a hybrid approach to operationalize D α so that the hesitation in an intuitionistic fuzzy number (IFN) can be further refined and characterized. Numerical experiments are carried out to demonstrate the features and novelty of the proposed approach compared to existing methods in the literature. The aim is to furnish an effective way to refine hesitations in intuitionistic fuzzy assessments for more reliable and confident decision aids

Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

Uncertainty and Congestion Elimination in 4G Network Call Admission Control using Interval Type-2 Intuitionistic Fuzzy Logic

The management and control of the global growth and complex nature of wireless Fourth Generation (4G) Networks elicits the need for Call Admission Control (CAC). However, CAC faces the challenge of network congestion, thereby deteriorating the network Quality of Service (QoS) due to inherent imprecision and uncertainties in the QoS data which leads to difficulties in measuring some objective and constraints of QoS using crisp values. Previous researches have shown the strength of Interval Type-2 Fuzzy Logic System (IT2FLS) in coping adequately with linguistic uncertainties. Intuitionistic fuzzy sets (IFSs) have indicated their ability to further reduce uncertainty by handling conflicting evaluation involving membership (M), nonmembership (NM) and hesitation. This paper applies the Interval Type-2 Intuitionistic Fuzzy Logic System (IT2IFLS) in solving CAC problem in order to achieve a better QoS in 4G Networks

Quality in crowdsourced experience-based evaluations : handling subjective responses

Experience-based evaluations (XBEs) are appraisals based on what someone has understood or learned about a topic by experience. Although XBEs can be highly subjective, imprecise, and diverse, information extracted from them can result in significant benefits for companies and organizations. However, handling XBEs can entail several challenges especially when potential data quality issues, such as a lack of reliability on XBEs provided by a large and heterogeneous group of (anonymous) sources, need to be handled. In this dissertation, challenges connected with the characterization, processing and quality of XBEs have been handled. Thereby, it is studied if and how existing and novel concepts and methods in the area of computational intelligence can be used to characterize and process XBEs in such a way that one can adequately handle data quality issues on subjective data provided by a large and heterogeneous group of respondents. It has been shown that existing and novel concepts and methods connected to fuzzy set theory, which aims to find approximate, achievable and robust solutions, can be used to address these challenges. Among the novel proposed concepts, augmented appraisal degrees and augmented (Atanassov) intuitionistic fuzzy sets are deemed to be the most important contributions of this dissertation