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Introduction to Special Issue on “Foundations and Applications of Granular Computing”
Author(s) -
Lin TsauYoung T. Y.,
Kudo Yasuo,
Miyamoto Sadaaki
Publication year - 2013
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21606
Subject(s) - citation , library science , state (computer science) , computer science , operations research , engineering , algorithm
Granular computing, by Zadeh’s words, is “a mode of computing in which the objects of computation are granular variables.” “Informally, a granule is a clump of elements of a universe of discourse which are drawn together by indistinguishability, similarity or proximity.” In practice, a granule has been interpreted as a piece of elementary knowledge, a region of uncertainty, and a module of systems. The concept of granules has appeared in various field, even though with different names, such as topology and neighborhood systems, fuzzy sets and rough sets, pattern recognition, machine learning, clustering, data mining, and many others. This special issue is aimed to introduce the recent improvement of foundations and applications of granular computing. All contributions are extended versions of the papers presented during the 2012 IEEE International Conference on Granular Computing, August 11–13, 2012, Hangzhou, People’s Republic of China. All contributions were also rigorously reviewed by peer-review and revised following to review results. We have the following five papers in this special issue: The first two papers explore the foundations of granular computing from two aspects of rough set theory; set-theoretical approximation of concepts and rule extraction from information systems. The first paper entitled “Knowledge Approximations in Binary Relation: Granular Computing Approach” by Zehua Chen, Tsau-Young (T. Y.) Lin, and Gang Xie introduces a new view of set theoretical approximation based on appropriately generalized interior and closure using binary relations. The second paper entitled “Division Charts as Granules and Their Merging Algorithm for Rule Generation in Nondeterministic Data” by Hiroshi Sakai, Mao Wu, and Michinori Nakata introduces a concept of division charts that describes data granules useful for generating rules. This paper also proposes a merging algorithm of division charts as a basis for generating rules from information systems.