A hybrid object based model combining probability and fuzzy set theories

  • Authors:

  • Tru H. Cao;Hoa Nguyen

  • Affiliations:

  • Faculty of Computer Science and Engineering, HCM City University of Technology, 268 Ly Thuong Kiet Street, HCM City, Vietnam.;Faculty of Information Technology, HCM City Open University, 97 Vo Van Tan Street, HCM City, Vietnam

  • Venue:
  • International Journal of Intelligent Information and Database Systems
  • Year:
  • 2007

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Abstract

Although there have been many fuzzy object-oriented data model proposed, and a bit less for probabilistic ones, models combining the relevance and strength of both fuzzy set theory and probability theory appear to be sporadic. This paper introduces our extension of Eiter et al.'s probabilistic object base model with two key features: uncertain and imprecise attribute values are represented as probability distributions on a set of fuzzy set values; class methods with uncertain and imprecise input and output arguments are formally integrated into the new model. A probabilistic interpretation of relations on fuzzy set values is proposed for their combination with probability degrees. Then the syntax and semantics of fuzzy-probabilistic object base schemas, instances, and selection operation are defined.