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Granular Computing

Granular Computing OnlineFirst articles

14.01.2019 | Original Paper

Maclaurin symmetric means of dual hesitant fuzzy information and their use in multi-criteria decision making

This paper investigates the Maclaurin symmetric mean (MSM) within the context of dual hesitant fuzzy sets and develops the dual hesitant fuzzy Maclaurin symmetric mean (DHFMSM), which can address the issues in previous dual hesitant fuzzy …

19.12.2018 | Original Paper

Distance and similarity measures for Pythagorean fuzzy sets

The concept of Pythagorean fuzzy sets is very much applicable in decision science because of its unique nature of indeterminacy. The main feature of Pythagorean fuzzy sets is that it is characterized by three parameters, namely, membership degree …

18.12.2018 | Original Paper

Examining stock index return with pattern recognition model based on cumulative probability-based granulating method by expert knowledge

In this paper, we apply an advanced pattern recognition model based on cumulative probability-based granulating method (Chen and Chen Inf Sci 346:261–274, 2016) using expert knowledge to examine its model efficiency further. The patterns of a bull …

11.12.2018 | Original Paper

Neighborhood attribute reduction approach to partially labeled data

Presently, from the viewpoint of rough set, most of the attribute reductions are only suitable for analyzing samples with complete labels. However, in many real-world applications, it is difficult to acquire the detailed labels of all samples, it …

10.12.2018 | Original Paper

Interval methods for robust gain scheduling controllers

An LMI-based approach

A novel interval-based approach for a gain-scheduled controller synthesis is presented in this paper which aims at stabilizing continuous-time dynamic systems of finite dimension in a guaranteed manner over predefined finitely long time horizons.

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Über diese Zeitschrift

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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