[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Interval Comparison Based on Dempster-Shafer Theory of Evidence

  • Conference paper
Parallel Processing and Applied Mathematics (PPAM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3019))

Abstract

The problem of crisp and fuzzy interval (number) comparison is of perennial interest, because of its direct relevance in practical modeling and optimization of real-world processes under uncertainty. There are many approaches to this problem presented in literature, but in all cases the authors propose the methods which give the result of interval comparison in form of real or Boolean number. On the other hand, it is easy to see that all arithmetic operations on intervals give us intervals. So, it seems quite natural to expect the result of interval comparison as interval as well. Indeed, when comparing intervals, we factually order the sets, and it should be preferable to get the result as the some type of set (interval). To do this, we propose the approach, which can derive us the results of comparison as the probability interval. For this purpose, we use the Dempster-Shafer theory of evidence with its probabilistic interpretation.

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 71.50
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 89.99
Price includes VAT (United Kingdom)
  • 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Wadman, D., Schneider, M., Schnaider, E.: On the use of interval mathematics in fuzzy expert system. International Journal of intelligent Systems 9, 241–259 (1994)

    Article  Google Scholar 

  2. Yager, R.R., Detyniecki, M., Bouchon–Meunier, B.: A context-dependent method for ordering fuzzy numbers using probabilities. Information Sciences 138, 237–255 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  3. Kundu, S.: Min-transitivity of fuzzy leftness relationship and its application to decision making. Fuzzzy Sets and Systems 86, 357–367 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  4. Krishnapuram, R., Keller, J.M., Ma, Y.: Quantitative analysis of properties and spatial relations of fuzzy image regions. IEEE Trans. Fuzzy Systems 1, 222–233 (1993)

    Article  Google Scholar 

  5. Nakamura, K.: Preference relations on set of fuzzy utilities as a basis for decision making. Fuzzy Sets and Systems 20, 147–162 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  6. Sengupta, T.K.P.: On comparing interval numbers. European Journal of Operational Research 127, 28–43 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  7. Kundu, S.: Preferance relation on fuzzy utilities based on fuzzy leftness relation on interval. Fuzzy Sets and Systems 97, 183–191 (1998)

    Article  MathSciNet  Google Scholar 

  8. Sevastjanov, P., Venberg, A.: Modeling and simulation of power units work under interval uncertainty. Energy 3, 66–70 (1998) (in Russian)

    Google Scholar 

  9. Sevastjanov, P., Venberg, A.: Optimization of technical and econmic parameters of power units work under fuzzy uncertainty. Energy 1, 73–81 (2000) (in Russian)

    Google Scholar 

  10. Sevastjanov, P.V., Rog, P.: A probabilistic approach to fuzzy and interval ordering. Task Quarterly, Special Issue ”Artificial and Computational Intelligence” 7, 147–156 (2003)

    Google Scholar 

  11. Sevastianov, P., Rog, P., Karczewski, K.: A Probabilistic Method for Ordering Group of Intervals. Computer Science, Czestochowa University of Technology 2, 45–53 (2002)

    Google Scholar 

  12. Sewastianow, P., Rog, P., Venberg, A.: The Constructive Numerical Method of Interval Comperison. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds.) PPAM 2001. LNCS, vol. 2328, pp. 756–761. Springer, Heidelberg (2002)

    Google Scholar 

  13. Dempster, A.P.: Upper and lower probabilities induced by a muilti-valued mapping. Ann. Math. Stat. 38, 325–339 (1967)

    Article  MATH  MathSciNet  Google Scholar 

  14. Dempster, A.P.: A generalization of Bayesian inference (with discussion). J. Roy. Stat. Soc., Series B 30, 208–247 (1968)

    MathSciNet  Google Scholar 

  15. Shafer, G.: A mathematical theory of evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  16. Yager, R.R., Kacprzyk, J., Fedrizzi, M.: Advances in Dempster-Shafer Theory of Evidence. Wiley, New York (1994)

    MATH  Google Scholar 

  17. Goodman, I.R., Nguyen, H.T.: Uncertainty Models for Knowledge-Based System. North-Holand, Amsterdam (1985)

    Google Scholar 

  18. Vasseur, P., Pegard, C., Mouaddib, E., Delahoche, L.: Perceptual organization approach based on Dempster-Shafer theory. Pattern Recognition 32, 1449–1462 (1999)

    Article  Google Scholar 

  19. Bloch, B.: Some aspects of Dempster-Shafer evidence theory for classification of multi-modality images taking partial volume effect into account. Pattern Recognition Letters 17, 905–919 (1996)

    Article  Google Scholar 

  20. Beynon, M.: DS/AHP method: A mathematical analysis, including an understanding of uncertainty. European Journal of Operational Research 140, 148–164 (2002)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sevastjanow, P. (2004). Interval Comparison Based on Dempster-Shafer Theory of Evidence. In: Wyrzykowski, R., Dongarra, J., Paprzycki, M., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2003. Lecture Notes in Computer Science, vol 3019. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24669-5_87

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24669-5_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21946-0

  • Online ISBN: 978-3-540-24669-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics