Skip to main content
SpringerLink
Log in
Book cover

On Fuzziness pp 311–323Cite as

Fuzzy Rule Based Systems as Tools towards Solving the “Key Problem of Engineering”

  • Chapter

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 298))

Abstract

Key problem of engineering? Is there anything that is called so? In order to explain what is meant by this, let me start with some references to teaching Digital Design for B.Sc. Electrical/Electronics Engineering students in the first grade. The key part of the standard curriculum of this subject is a series of design algorithms for combinational and sequential circuits, even though it is obvious nowadays that the algorithmic design of LSI digital circuitry is a mathematically intractable problem that always leads to NP-hardness, and thus to insolvability in the classic sense. Learning the well established design approaches that have served well for SSI circuits in the early times of Digital Design nevertheless teaches a way of looking at the problems in a way that helps with finding reasonably good, or almost optimal solutions that can be very well used in the engineering practice and that might be applied in commercially feasible products, even in the case of more complex problems, up to the MSI level; while at the same time it teaches the students to think engineering optimization and design.

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   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover 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. Baranyi, P., Koczy, L.T., Gedeon, T.D.: A Generalized Concept for Fuzzy Rule Interpolation. IEEE Transactions on Fuzzy Systems 12(6), 820–832 (2004)

    Article  Google Scholar 

  2. Burkhardt, D.G., Bonissone, P.P.P.: Automated Fuzzy Knowledge Base Generation and Tuning. In: Proceedings of the FUZZ-IEEE 1992 – First IEEE International Conference Fuzzy Systems, San Diego, CA, pp. 179–196 (1992)

    Google Scholar 

  3. Ding, L., Shen, Z., Mukaidono, M.: Principle for Approximate Reasoning-based on Revision Principle. In: Fuzzy Logic Systems Institute (publ.): Proceedings of the 2nd International Conference on Fuzzy Logic and Neural Networks, IIZUKA 1992, Iizuka, Fukuoka, Japan, pp. 305–308 (1992)

    Google Scholar 

  4. Dubois, D., Prade, H.: Gradual Rules in Approximate Reasoning. Information Sciences 61(1-2), 103–122 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  5. Huang, Z., Shen, Q.: Fuzzy Interpolation and Extrapolation: A Practical Approach. IEEE Transactions on Fuzzy Systems 16(1), 13–28 (2008)

    Article  Google Scholar 

  6. Klahr, D., Langley, P.W., Neches, R.T.: Production System Models of Learning and Development. The MIT Press, Cambridge (1987)

    Google Scholar 

  7. Novák, V.: Fuzzy Sets and Their Applications. Adam Hilger, Bristol (1989)

    MATH  Google Scholar 

  8. Koczy, L.T., Hirota, K.: Ordering, Distance and Closeness of Fuzzy Sets. Fuzzy Sets and Systems 59(3), 281–293 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  9. Koczy, L.T., Hirota, K.: Approximate Reasoning by Linear Rule Interpolation and General Approximation. International Journal of Approximate Reasoning 9(3), 197–225 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  10. Koczy, L.T., Hirota, K.: Interpolative Reasoning with Insufficient Evidence in Sparse Fuzzy Rule Bases. Information Sciences 71(1-2), 169–201 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  11. Koczy, L.T., Hirota, K.: Approximative Inference in Hierarchical Structured Rule Bases. In: 5th IFSA World Congress (IFSA 1993), Seoul, pp. 1262–1265 (1993)

    Google Scholar 

  12. Koczy, L.T.: Fuzzy if...then rule models and their transformation into one another. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 26(5), 621–637 (1996)

    Article  Google Scholar 

  13. Koczy, L.T., Hirota, K., Muresan, L.: Interpolation in Hierarchical Fuzzy Rule Bases. International Journal of Intelligent Fuzzy Systems 1(2), 77–84 (1999)

    MathSciNet  Google Scholar 

  14. Kovács, S., Koczy, L.T.: Shape of Fuzzy Conclusion Generated by Linear Interpolation of Trapezoidal if...then... Rules, vol. 6, pp. 83–93. Tatra Mountains Mathematical Publications (1995)

    Google Scholar 

  15. Mamdani, E.A., Assilian, S.: An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller. International Journal of Man-Machine Studies 7(1), 1–13 (1975)

    Article  MATH  Google Scholar 

  16. Marks II, R.J.: Introduction to Shannon Sampling and Interpolation Theory. Springer, New York (1991)

    Book  MATH  Google Scholar 

  17. Qiao, W.Z., Mizumoto, M., Shi, Y.: An Improvement to Koczy and Hirota’s Interpolative Reasoning in Sparse Fuzzy Rule Bases. International Journal of Approximate Reasoning 15, 195–201 (1996)

    MathSciNet  Google Scholar 

  18. Shi, Y., Mizumoto, M.: On Koczy’s Interpolative Reasoning Method in Sparse Fuzzy Rule Bases. In: Proceedings of the 10th Fuzzy Systems Symposium, Osaka, Japan, pp. 221–224 (1994)

    Google Scholar 

  19. Sugeno, M., Griffin, M.F., Bastian, A.: Fuzzy Hierarchical Control of an Unmanned Helicopter. In: Proceedings of the 5th IFSA World Congress, Seoul, Korea, pp. 179–182 (1993)

    Google Scholar 

  20. Sugeno, M., Yasukawa, T.: A Fuzzy-logic-based Approach to Qualitative Modeling. IEEE Transactions on Fuzzy Systems 1(1), 7–31 (1993)

    Article  Google Scholar 

  21. Takagi, T., Sugeno, M.: Fuzzy Identification of Systems and its Applications to Modeling and Control. IEEE Transactions on Systems, Man, and Cybernetics SMC-15(1), 116–132 (1985)

    Article  MATH  Google Scholar 

  22. Tikk, D., Joó, I., Koczy, L.T., Várlaki, P., Moser, B., Gedeon, T.D.: Stability of Interpolative Fuzzy KH Controllers. Fuzzy Sets and Systems 125(1), 105–119 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  23. Türksen, I.B., Zhao, Z.-Q.: An Approximate Analogical Reasoning Approach Based on Similarity Measures. IEEE Transactions on Systems, Man, and Cybernetics 18(6), 1049–1056 (1988)

    Article  Google Scholar 

  24. Waterman, D.A., Hayes-Roth, F.: Pattern-Directed Inference Systems. Academic Press, New York (1978)

    MATH  Google Scholar 

  25. Yam, Y., Koczy, L.T.: Representing Membership Functions as Points in High-dimensional Spaces for Fuzzy Interpolation and Extrapolation. IEEE Transactions on Fuzzy Systems 8(6), 761–772 (2000)

    Article  Google Scholar 

  26. Yang, L., Shen, Q.: Adaptive Fuzzy Interpolation. IEEE Transactions on Fuzzy Systems 19(6), 1107–1126 (2011)

    Article  Google Scholar 

  27. Zadeh, L.A.: Fuzzy Sets. Information and Control 8(3), 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  28. Zadeh, L.A.: Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics SMC-3(1), 28–44 (1973)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Szechenyi Istvan University (Gyor) and Budapest University of Technology and Economics, Budapest, Hungary

    Laszlo T. Koczy

Authors
  1. Laszlo T. Koczy
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. , Edificio de Investigación, European Centre for Soft Computing, C Gonzalo Gutiérrez Quirós S/N, Mieres, 33600, Spain

    Rudolf Seising

  2. Edificio de Investigación, 3ª Planta., European Centre for Soft Computing, C Gonzalo Gutiérrez Quirós S/N, Mieres, 33600, Asturias, Spain

    Enric Trillas

  3. Edificio de Investigación, 3ª Planta., European Centre for Soft Computing, Asturias, Mieres, 33600, Spain

    Claudio Moraga

  4. , Department of Mathematic and Informatics, Università di Palermo, Via Archirafi 34, Palermo, 90123, Italy

    Settimo Termini

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Koczy, L.T. (2013). Fuzzy Rule Based Systems as Tools towards Solving the “Key Problem of Engineering”. In: Seising, R., Trillas, E., Moraga, C., Termini, S. (eds) On Fuzziness. Studies in Fuzziness and Soft Computing, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35641-4_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35641-4_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35640-7

  • Online ISBN: 978-3-642-35641-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation