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Granular Computing

Granular Computing OnlineFirst articles

27.05.2020 | Original Paper Open Access

Event abstraction in process mining: literature review and taxonomy

The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., the focus of process mining, yields a detailed …

25.04.2020 | Original Paper Open Access

A novel approach of linguistic intuitionistic cubic hesitant variables and their application in decision making

In this paper, we proposed the notion of linguistic intuitionistic cubic hesitant variables and defined some aggregation operators to deal with uncertainties in the form of linguistic intuitionistic cubic hesitant variables (LICHVs). LICHVs …

22.04.2020 | Original Paper

Decision-making approach based on Pythagorean Dombi fuzzy soft graphs

A Pythagorean fuzzy set model is more useful than intuitionistic fuzzy set model to handle the imprecise information involving both membership and nonmembership degrees, and a soft set is an other parameterized point of view for handling the …

07.04.2020 | Original Paper

Complex Pythagorean Dombi fuzzy graphs for decision making

A complex Pythagorean fuzzy set (CPFS) is the generalization of Pythagorean fuzzy set (PFS) in which the range of degrees is extended from [0, 1] to complex plane with unit disk. The averaging operators play a significant role to transform the …

24.03.2020 | Original Paper

Knowledge measure and entropy: a complementary concept in fuzzy theory

The knowledge measure can be considered as a dual measure of entropy for fuzzy sets. In the present work, a new entropy-based knowledge measure is proposed for FSs, which complies with the extended idea of De Luca and Termini axioms. Besides this …

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Granular Computing constitutes an extensive body of knowledge, which dwells upon individual formalisms of information granules (established within various settings including set theory, interval calculus, fuzzy sets, rough sets, shadowed sets, probabilistic granules) and unifies them to form a coherent methodological and developmental environment. Granular Computing is about formation, processing and communicating information granules.

Aims The Journal of Granular Computing provides a rapid dissemination of timely and important results. The aim is to bring recent advances in the dynamically expanding area including its fundamentals, algorithmic developments, and applications. It supports the integration of theoretical and practical results leading to advanced applications. The journal establishes an international forum and aims to address the needs of the academic community as well as to appeal to practitioners and graduate students by publishing time-to-time review material and surveys. It serves as a platform fostering comparisons, extensions, and innovative applications.

The scope The journal covers a broad spectrum of subjects of Granular Computing embracing the theory, methodology, and applied side of the discipline including case studies. Theoretical and applied studies involving fuzzy sets, interval analysis, rough sets, shadowed sets, probabilistic sets yet well positioned in the synergistic setup of Granular Computing and making reference to the fundamentals of the area are welcome.

Several categories of manuscripts are considered including regular papers, correspondences, reviews and case studies.

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