Skip to main content
SpringerLink
Log in
Book cover

Brazilian Symposium on Artificial Intelligence

SBIA 2002: Advances in Artificial Intelligence pp 386–396Cite as

Restoring Consistency in Systems of Fuzzy Gradual Rules Using Similarity Relations

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2507))

Abstract

We present here a method that uses similarity relations to restore consistency in fuzzy gradual rules systems: we propose to transform potentially inconsistent rules by making their consequents more imprecise. Using a suitable similarity relation we obtain consistent rules with a minimum of extra imprecision. We also present an application to illustrate the approach.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Driankov, D., Hellendoorn, H., Reinfrank, M. An Introduction to Fuzzy Control. Springer-Verlag, 1996.

    Google Scholar 

  2. Dubois D., Prade H. What are fuzzy rules and how to use them. Fuzzy Sets and Systems 84, 169–185, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  3. Dubois D., Prade H., Ughetto L. Coherence of Fuzzy Knowledge Bases. In Proc. Fuzz-IEEE’96, New Orleans (USA), 1858–1864, 1996.

    Google Scholar 

  4. Dubois D., Prade H., Ughetto L. Checking the coherence and redundancy of fuzzy knowledge bases. In IEEE Trans. on Fuzzy Systems 5(3), 398–417, 1997.

    Article  Google Scholar 

  5. Godo L., Sandri S. A similarity-based approach to deal with inconsistency in systems of fuzzy gradual rules. In Proc. of IPMU’02, Annecy (France), 1655–1662, 2002.

    Google Scholar 

  6. Gottwald S., Petri U. An algorithmic approach towards consistency checking for systems of fuzzy control rules. In Proc. of EUFIT’95, Aachen (Germany) 28–31, 1995.

    Google Scholar 

  7. Pedrycz W., Gomide F. An introduction to Fuzzy sets: Analysis and Design. MIT Press, 1998.

    Google Scholar 

  8. Perfilieva I., Tonis A. Compatibility of systems of fuzzy relations equations. In Int. Journal of General Systems 29(4), 511–528, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  9. Takagi T., Sugeno T. Fuzzy identification of systems and its aplication to modeling and control. IEEE Trans. on Systems, Man and Cibernetics 15, 116–132, 1985.

    MATH  Google Scholar 

  10. Weisbrod J., Fantana N. L. Detecting local inconsistency and incompleteness in fuzzy rule bases. In Proc. EUFIT’96, Aachen (Germany) 656–660, 1996.

    Google Scholar 

  11. Yager R. R., Larsen H. L. On discovering potential inconsistencies in validating uncertain knowledge bases by reflecting on the input. IEEE Trans. on S. M. C. 21, 790–801, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  12. Yu W., Bien Z. Design of fuzzy logic controller with inconsistent rule base. Journal of Intelligent and Fuzzy Systems 2, 147–159, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. LAC - INPE, 12201-970, S.J. Campos, Brazil

    Isabela Drummond & Sandra Sandri

  2. IIIA - CSIC, 08193, Bellaterra, Spain

    Lluis Godo & Sandra Sandri

Authors
  1. Isabela Drummond
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lluis Godo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sandra Sandri
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Departamento de Automação e Sistemas, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, SC, Brazil

    Guilherme Bittencourt

  2. Centro de Informática, Universidade Federal de Pernambuco, Cx. Postal 7851, 50732-970, Recife, PE, Brazil

    Geber L. Ramalho

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Drummond, I., Godo, L., Sandri, S. (2002). Restoring Consistency in Systems of Fuzzy Gradual Rules Using Similarity Relations. In: Bittencourt, G., Ramalho, G.L. (eds) Advances in Artificial Intelligence. SBIA 2002. Lecture Notes in Computer Science(), vol 2507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36127-8_37

Download citation

  • DOI: https://doi.org/10.1007/3-540-36127-8_37

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00124-9

  • Online ISBN: 978-3-540-36127-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation