The Scientific World Journal

Theory and Application on Rough Set, Fuzzy Logic, and Granular Computing

Publishing date
27 Mar 2015
Submission deadline
07 Nov 2014

Lead Editor
Guest Editors

1Jiangsu University of Science and Technology, Zhenjiang, China

2Chongqing University of Technology, Chongqing, China

3University of Regina, Regina, Canada

Theory and Application on Rough Set, Fuzzy Logic, and Granular Computing


Recently, the rough set and fuzzy set theory have generated a great deal of interest among more and more researchers. Granular computing is an emerging computing paradigm of information processing and an approach for knowledge representation and data mining. The advances of rough set theory and fuzzy logic have greatly influenced the development of granular computing. Specifically, the philosophy and methodology of rough sets and fuzzy sets, centralized on the notions of indiscernibility and knowledge granularity, are fundamental to granular computing. It is fair to say that the plentiful results and applications of the theory of rough sets and fuzzy sets motivate many researchers to study granular computing. The art of granular computing can be fully appreciated from the philosophical perspective as structured thinking, from the methodological perspective as structured problem solving, and from the computational perspective as structured information processing.

The aim of this special issue is to encourage researchers in related areas to discuss and communicate the latest advancements of rough set, fuzzy logic, and granular computing, which cover both theoretical and practical results. Contributions containing new insights and findings in rough set, fuzzy logic, and granular computing are welcome.

Potential topics include, but are not limited to:

  • Logical and mathematical theory of rough sets
  • Generalization of rough sets
  • Fuzzy logic and fuzzy system
  • Formal concept analysis
  • Soft computing and applications
  • Algorithms design and analysis of granular computing
  • Uncertainty in granular computing and complex data processing
  • Expert system and machine learning
  • Knowledge discovery and data mining


  • Special Issue
  • - Volume 2015
  • - Article ID 967350
  • - Editorial

Theory and Application on Rough Set, Fuzzy Logic, and Granular Computing

Xibei Yang | Weihua Xu | Yanhong She
  • Special Issue
  • - Volume 2014
  • - Article ID 617162
  • - Research Article

Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model

Weiying Wang | Zhiqiang Xu | ... | Wei Wu
  • Special Issue
  • - Volume 2014
  • - Article ID 307468
  • - Research Article

On Distribution Reduction and Algorithm Implementation in Inconsistent Ordered Information Systems

Yanqin Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 927014
  • - Research Article

Further Study of Multigranulation -Fuzzy Rough Sets

Wentao Li | Xiaoyan Zhang | Wenxin Sun
  • Special Issue
  • - Volume 2014
  • - Article ID 317387
  • - Research Article

Approximation Set of the Interval Set in Pawlak's Space

Qinghua Zhang | Jin Wang | ... | Feng Hu
  • Special Issue
  • - Volume 2014
  • - Article ID 783940
  • - Research Article

A Novel Method of the Generalized Interval-Valued Fuzzy Rough Approximation Operators

Tianyu Xue | Zhan’ao Xue | ... | Tailong Zhu
  • Special Issue
  • - Volume 2014
  • - Article ID 382439
  • - Research Article

δ-Cut Decision-Theoretic Rough Set Approach: Model and Attribute Reductions

Hengrong Ju | Huili Dou | ... | Jingyu Yang
The Scientific World Journal
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Acceptance rate15%
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