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.
- Covers the dynamic field of granular computing, including fundamentals, algorithmic developments and applications
- Spans theory, methodology and applied aspects of the discipline
- Publishes regular papers, correspondence, reviews and case studies
- Witold Pedrycz,
- Shyi-Ming Chen
- Publishing model
- Hybrid. Open Access options available
- 26 days
- Submission to first decision
- 132 days
- Submission to acceptance
- 32,971 (2019)
A new approach to similarity measure for generalized trapezoidal fuzzy numbers and its application to fuzzy risk analysis
Authors (first, second and last of 4)
About this journal
- Electronic ISSN
- Print ISSN
- Abstracted and indexed in
- EBSCO Discovery Service
- Google Scholar
- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- OCLC WorldCat Discovery Service
- ProQuest-ExLibris Primo
- ProQuest-ExLibris Summon