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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2010: Artifical Intelligence and Soft Computing pp 659–666Cite as

The Normalization of the Dempster’s Rule of Combination

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6114))

Abstract

A new method for normalization and combination of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence based on the so-called ”interval extended zero” method is proposed. The two desirable intuitively obvious properties of normalization procedure are defined. The main of them is based on the assumption that the sum of normalized intervals should be an interval centered around 1 with a minimal width. The advantages of a new method are illustrated with use of numerical examples. It is shown that a new method performs better than known methods for combination of interval-valued belief structures as it provides the results with the properties which are close to the desirable ones.

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References

  1. Cleary, J.C.: Logical Arithmetic. Future Computing Systems 2, 125–149 (1987)

    Google Scholar 

  2. Denoeux, T.: Reasoning with imprecise belief structures. Internat. J. Approx. Reason. 20, 79–111 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  3. Moore, R.E.: Interval analysis. Prentice-Hall, Englewood Cliffs (1966)

    MATH  Google Scholar 

  4. Sevastjanov, P., Dymova, L.: Fuzzy solution of interval linear equations. In: Procedings of 7th Int. Conf. Paralel Processing and Applied Mathematics, Gdansk, pp. 1392–1399 (2007)

    Google Scholar 

  5. Sevastjanov, P., Dymova, L.: A new method for solving interval and fuzzy equations: linear case. Information Sciences 17, 925–937 (2009)

    Article  MathSciNet  Google Scholar 

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

    MATH  Google Scholar 

  7. Wang, Y.M., Elhag, T.M.S.: On the normalization of interval and fuzzy weights. Fuzzy Sets and Systems 157 2456, 2456–2471 (2006)

    Article  MathSciNet  Google Scholar 

  8. Wang, Y.M., Yang, J.B., Xu, D.L., Kwai-Sang, C.: On the combination and normalization of interval-valued belief structures. Information Sciences 177, 1230–1247 (2007)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Comp.& Information Sci., Czestochowa University of Technology, Dabrowskiego 73, 42-200, Czestochowa, Poland

    Pavel Sevastjanov, Pavel Bartosiewicz & Kamil Tkacz

Authors
  1. Pavel Sevastjanov
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  2. Pavel Bartosiewicz
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  3. Kamil Tkacz
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Academy of Humanities and Economics in Łódź, ul. Rewolucji 1905 nr 64, Łódź, Poland

    Rafał Scherer

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley Initiative in Soft Computing (BISC), 94720-1776, CA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory Department of Electrical and Computer Engineering, University of Louisville, 40292, Louisville, KY

    Jacek M. Zurada

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sevastjanov, P., Bartosiewicz, P., Tkacz, K. (2010). The Normalization of the Dempster’s Rule of Combination. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artifical Intelligence and Soft Computing. ICAISC 2010. Lecture Notes in Computer Science(), vol 6114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13232-2_81

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  • DOI: https://doi.org/10.1007/978-3-642-13232-2_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13231-5

  • Online ISBN: 978-3-642-13232-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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