Uncertainty evaluation via fuzzy entropy for multiple facts

Sanghyuk Lee, T. O. Ting

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The fuzzy entropy designed for multiple facts selection has been carried out in this work. The entropy for the fuzzy data with respect to a specified fact is designed through a distance measure method. The obtained fuzzy entropy is then applied for the selection from multiple facts. From the relevant fuzzy entropy, it is concluded that data uncertainty information is limited by the total fact of n-1. The bounded calculation of data uncertainty to each fact is proven for multiple facts, and the decision of fuzzy data to the certain fact among multiple facts has been considered with the assistance of fuzzy entropy calculation.

Original languageEnglish
Pages (from-to)345-354
Number of pages10
JournalInternational Journal of Electronic Commerce Studies
Volume4
Issue number2
DOIs
Publication statusPublished - 2013

Keywords

  • Decision making
  • Fuzzy entropy
  • Multiple facts
  • Similarity measure

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