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Fuzzy System Modeling and Representation Based on Linguistic Variable Ontology and SWRL

초록

영어

Ontology is an important tool on the semantic web, for ontology has a powerful expressive ability on knowledge representation. However, it has no ability to represent the imprecise information as well as the uncertainty. In order to share and deal with the fuzzy knowledge between homogeneous systems on the semantic web, in this paper, the concept of linguistic variable ontology is proposed as the basis of Fuzzy System. Taking a flu fuzzy diagnosis case for example, fuzzy system is modeled. For fuzzy knowledge representation and further inference, the fuzzy rule base is constructed, which constitutes a part of fuzzy system. A tool of protégé is used to realize the fuzzy system and a plugin of SWRLTab for the fuzzy rule. Also, SWRL/OWL is used to represent the rules formally for facilitating machine understanding and process. Comparisons are made between two fuzzy tools to illustrate the advantages of SWRLTab. The paper concludes that linguistic variable ontology-based diagnosis system can achieve the fuzzy knowledge sharing between homogeneous systems correctly.

목차

Abstract
 1. Introduction
 2. Definitions of Linguistic Variable Ontology
  2.1. Fuzzy linguistic variable
  2.2. Fuzzy linguistic variable ontology
  2.3. Extended ontology
  2.4. Basic fuzzy ontology
 3. Modeling of Fuzzy System
  3.1. Building Flu Fuzzy Diagnosis System model
  3.2. Using protégé to realize the fuzzy system
  3.3. Fuzzy rule representation in SWRL/OWL
 4. Experiment comparison and analysis
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Yiduo Liang Traffic Transportation and Management College, Dalian Maritime University, China
  • Jun Zhai Traffic Transportation and Management College, Dalian Maritime University, China
  • Jianfeng Li Traffic Transportation and Management College, Dalian Maritime University, China

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