Granular Computing

Aims & 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 well positioned in the synergistic setup of Granular Computing and making reference to the fundamentals of the area are welcome.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	1.169

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	51

Impact Factor

Year	Value
2024	0.00

Journal Rank

Year	Value
2024	3716

Journal Citation Indicator

Year	Value
2024	1565

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• A triarchic theory of granular computing

  Citation: 207

  Authors: Yiyu

• Intuitionistic fuzzy Dombi aggregation operators and their application to multiple attribute decision-making

  Citation: 176

  Authors: Mijanur Rahaman, Utpal

• Managing multi-granularity linguistic information in qualitative group decision making: an overview

  Citation: 145

  Authors: Zeshui, Hai

• Interactive granular computing

  Citation: 140

  Authors: Andrzej, Andrzej, Soma

• A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of a linguistic term for computing with words

  Citation: 122

  Authors: Jerry M.

• Semi-random partitioning of data into training and test sets in granular computing context

  Citation: 119

  Authors: Han, Mihaela

• Granular computing: from granularity optimization to multi-granularity joint problem solving

  Citation: 117

  Authors: Guoyin, Jie, Ji

• Distance and similarity measures for Pythagorean fuzzy sets

  Citation: 116

  Authors: Paul Augustine

• Event abstraction in process mining: literature review and taxonomy

  Citation: 115

  Authors: Sebastiaan J., Felix, Massimiliano, Agnes

• DCC: a framework for dynamic granular clustering

  Citation: 115

  Authors: Georg, Richard

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