Dominance-based fuzzy rough set analysis of uncertain and possibilistic data tables

Tuan Fang Fan, Churn Jung Liau*, Duen-Ren Liu

*Corresponding author for this work

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

In this paper, we propose a dominance-based fuzzy rough set approach for the decision analysis of a preference-ordered uncertain or possibilistic data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two objects based on their imprecise evaluations with respect to each criterion. This results in a valued dominance relation on the universe. Then, we define the degree of adherence to the dominance principle by every pair of objects and the degree of consistency of each object. The consistency degrees of all objects are aggregated to derive the quality of the classification, which we use to define the reducts of a data table. In addition, the upward and downward unions of decision classes are fuzzy subsets of the universe. Thus, the lower and upper approximations of the decision classes based on the valued dominance relation are fuzzy rough sets. By using the lower approximations of the decision classes, we can derive two types of decision rules that can be applied to new decision cases.

Original languageEnglish
Pages (from-to)1283-1297
Number of pages15
JournalInternational Journal of Approximate Reasoning
Volume52
Issue number9
DOIs
StatePublished - 1 Dec 2011

Keywords

  • Dominance-based rough set approach
  • Multi-criteria decision analysis
  • Possibilistic data table
  • Preference-ordered data tables
  • Rough set theory
  • Uncertain data tables

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