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Published 02.01.2024

Call for papers Four Decades of Rough Set Theory: Achievements and Future

Call for papers
Four Decades of Rough Set Theory: Achievements and Future
Special Issue in: Applied Soft Computing

 

More than forty years ago, Professor Zdzisław Pawlak introduced the Rough Set Theory (RST) for data analysis and knowledge exploration. Today RST is one of the leading paradigms in Soft Computing and Artificial Intelligence, with a wide range of applications. It has been applied in many AI-based systems and research areas, such as granular computing, machine learning, pattern recognition, uncertain reasoning, etc.

 

 

Guest editors:

 

Prof. Usman Qamar,
National University of Sciences and Technology (NUST), Pakistan
Email: usmanq@ceme.nust.edu.pk

Prof. Dominik Slezak,
University of Warsaw, Poland
Email: slezak@mimuw.edu.pl

Prof. Yiyu Yao,
University of Regina, Canada
Email: yiyu.yao@uregina.ca 

Prof. John Ahmet Erkoyuncu,
Cranfiled University, UK,
Email: j.a.erkoyuncu@Cranfield.ac.uk 

 

Applied Soft Computing journal submission information:

 

The introduction of rough set theory (RST) by Professor Zdzisław Pawlak has been over 40years. The theory has attracted many researchers worldwide. RST has many advantages overits counterparts including efficient algorithms for finding hidden patterns in data, generationof optimal sets decision rules from data, easy-to-interpret results and suitable for parallel processing. Rough set approaches are of fundamental importance in Soft Computing, Artificial Intelligence, and Data Science, especially in data mining, knowledge discovery, decision support systems, expert systems, cognitive systems, and autonomous systems. We welcome studies and contributions on the historical progress of RST, the current and novel research on RST, and the future directions of RST.

 

Topics of Interest:

  • Past achievements of RST
  • Classical RST
  • RST and granular computing
  • RST and soft computing
  • Bayesian rough sets
  • Decision-theoretic rough sets
  • Dominance-based rough sets
  • Game-theoretic rough sets
  • Neighborhood based rough sets
  • Probabilistic rough sets
  • Variable precision rough sets
  • Fuzzy rough sets and rough fuzzy sets
  • Integration of RST into AI
  • RST decision rules for explanatory models for AI

 

SI Proposal Form

  • RST for data mining
  • RST for machine learning
  • RST for operational research
  • RST for big data and data science
  • Three-way decision
  • Applications of RST
  • Challenges in RST
  • Future of RST


Important dates

Submissions Open: December 1, 2023
Submissions Deadline: April 30, 2024
Publication Date: 2024

 

 

Journal webpage: https://www.sciencedirect.com/journal/applied-soft-computing/about/call-for-papers#four-decades-of-rough-set-theory-achievements-and-future