Special issue on granular computing for cognitive computing in engineering applications

Published 31 May, 2022


Granular computing is a newly-developed paradigm in the area of human-inspired computing. It takes full advantage of data abstraction and reasoning at multiple levels of granularity; as a result, many engineering applications can be well addressed via formulating and communicating information granules. Since the birth of granular computing, many cognitive-computing-inspired mathematical tools have been explored, such as fuzzy sets, rough sets, three-way decisions, formal concept analysis, quotient space and cloud models.

By using the superiorities of granular computing, we can depict, fuse and analyse numerous complex engineering problems from the perspective of cognitive computing, boosting the applicability and efficiency of problem solving. But it remains necessary to collect and investigate viable granular computing models and methods for cognitive computing in engineering applications that own big scientific advances and significant application values.

The aim of this special issue is to further the interaction of granular computing and cognitive computing in engineering applications. We solicit state-of-the-art studies that introduce a new research direction in granular-computing-based cognitive computing. Original research work, significantly extended versions of conference papers and review papers are welcome.  


These will include, but not be limited to:

  • Cognitive theory and engineering applications of rough sets
  • Cognitive three-way decisions in engineering applications
  • Uncertainty in cognitive granular computing and engineering data processing
  • Cognitive machine learning methods for engineering applications
  • Cognitive analysis in engineering knowledge discovery and data mining
  • Other emerging cognitive tools in engineering applications

Important deadlines:

  • Submission deadline: 30 November 2022
  • Publication date:  31 March 2023

Submission instructions:

Please read the Guide for Authors  before submitting. All articles should be submitted online; please select SI: GCCCEA on submission.

Guest Editors:

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