A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance

Authors

  • Nguyen Van Thien Hanoi University of Industry, Vietnam
  • Janos Demetrovics Institute for Computer and Control (SZTAKI) Hungarian Academy of Sciences
  • Vu Duc Thi Institute of Information Technology VNU, Vietnam
  • Nguyen Long Giang Institute of Information Technology VNU, Vietnam
  • Nguyen Nhu Son Institute of Information Technology VNU, Vietnam

DOI:

https://doi.org/10.55630/sjc.2016.10.13-30

Keywords:

granular computing, fuzzy granular structure, fuzzy information granule, fuzzy information granularity, fuzzy distance

Abstract

In fuzzy granular computing, a fuzzy granular structure is the collection of
fuzzy information granules and fuzzy information granularity is used to
measure the granulation degree of a fuzzy granular structure.

In general, the fuzzy information granularity characterizes discernibility ability
among fuzzy information granules in a fuzzy granular structure. In recent years,
researchers have proposed some concepts of fuzzy information granularity based
on partial order relations. However, the existing forms of fuzzy information granularity
have some limitations when evaluating the fineness/coarseness between two fuzzy
granular structures. In this paper, we propose an extension of fuzzy information
granularity based on a fuzzy distance measure.

We prove theoretically and experimentally that the proposed fuzzy information
granularity is the best one to distinguish fuzzy granular structures.

ACM Computing Classification System (1998): I.5.2, I.2.6.

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Published

2017-02-17

Issue

Vol. 10 No. 1 (2016)

Section

Articles