Dominance-based rough set model in intuitionistic fuzzy information systems

  • Authors:

  • Bing Huang;Hua-xiong Li;Da-kuan Wei

  • Affiliations:

  • School of Information Science, Nanjing Audit University, Nanjing 211815, PR China and Information Systems Auditing Experimental Center, Nanjing Audit University, Nanjing 211815, PR China;School of Engineering & Management, Nanjing University, Nanjing 210093, PR China;School of Information Engineering, Hunan Science and Technology University, Yongzhou 425100, PR China

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2012

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Abstract

Intuitionistic fuzzy information systems are generalized types of conventional fuzzy-valued information systems. By introducing a dominance relation to intuitionistic fuzzy information systems, we propose a notion of dominance intuitionistic fuzzy information systems (DIFIS) and establish a dominance-based rough set model, which is mainly based on the substitution of the indiscernibility relation in classic rough set theory by a dominance relation that is defined on the score and accuracy function of intuitionistic fuzzy value in DIFIS. Furthermore, to simplify the knowledge representation and extract useful and simpler dominance intuitionistic fuzzy rules, we provide two attribute reduction approaches to eliminate the redundant information. Finally, we apply these approaches to computer auditing risk assessment, and by using an application as a case study we acquire some valuable assessment rules. These resulting rules can provide an available method to acquire knowledge from DIFISs.