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An Optimal Unified Combination Rule

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Belief Functions: Theory and Applications (BELIEF 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8764))

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Abstract

This paper presents an optimal unified combination rule within the framework of the Dempster-Shafer theory of evidence to combine multiple bodies of evidence. It is optimal in the sense that the resulting combined m-function has the least dissimilarity with the individual m-functions and therefore represents the greatest amount of information similar to that represented by the original m-functions. Examples are provided to illustrate the proposed combination rule.

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Author information

Authors and Affiliations

  1. Scientific Computing and Imaging Institute, Salt Lake City, Utah, USA

    Yanyan He

  2. Department of Mathematics, Florida State University, Tallahassee, FL, USA

    M. Yousuff Hussaini

Authors
  1. Yanyan He
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  2. M. Yousuff Hussaini
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Editor information

Editors and Affiliations

  1. Department of Computing and Communications Technologies, Oxford Brookes University, Wheatley Campus, OX33 1HX, Oxford, UK

    Fabio Cuzzolin

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© 2014 Springer International Publishing Switzerland

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He, Y., Hussaini, M.Y. (2014). An Optimal Unified Combination Rule. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-11191-9_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11190-2

  • Online ISBN: 978-3-319-11191-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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