Credible rules in incomplete decision system based on descriptors

  • Authors:

  • Xibei Yang;Jun Xie;Xiaoning Song;Jingyu Yang

  • Affiliations:

  • School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China and School of Computer Science and Telecommunication Engineering, Jiangsu ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China and School of Electronics and Information, Jiangsu University of Science ...;School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, PR China

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2009

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Abstract

This paper proposes a new approach to knowledge acquisition in the incomplete decision system with preference-ordered domains of attributes. In such incomplete system, the concepts of @6 and @7 descriptors are proposed. Two types of certain rules, @6 and @7 ''credible rules'' are then generated by using the @6 and @7 descriptors. With introduction of the relative reducts of @6 and @7 descriptors into the incomplete decision system, @6 and @7 ''optimal credible rules'' are further proposed. The judgment theorems and discernibility functions associated with the relative reducts of @6 and @7 descriptors are also obtained, from which we can derive @6 and @7 ''optimal credible rules'' from the incomplete decision system. Some numerical examples are employed to substantiate the conceptual arguments.