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Introduction to the ER Rule for Evidence Combination

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7027))

Abstract

The Evidential Reasoning (ER) approach has been developed to support multiple criteria decision making (MCDM) under uncertainty. It is built upon Dempster’s rule for evidence combination and uses belief functions for dealing with probabilistic uncertainty and ignorance. In this introductory paper, following a brief introduction to Dempster’s rule and the ER approach, we report the discovery of a new generic ER rule for evidence combination [16]. We first introduce the concepts and equations of a new extended belief function and then examine the detailed combination equations of the new ER rule. A numerical example is provided to illustrate the new ER rule.

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Authors and Affiliations

  1. Manchester Business School, The University of Manchester, Manchester, M15 6PB, UK

    Jian-Bo Yang & Dong-Ling Xu

Authors
  1. Jian-Bo Yang
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  2. Dong-Ling Xu
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Editor information

Editors and Affiliations

  1. College of Computer Science, Zhejiang University, 310027, Hangzhou, Zhejiang Province, P.R. China

    Yongchuan Tang

  2. Japan Advanced Institute of Science and Technology (JAIST), 923-1292, Tatsunokuchi, Ishikawa, Japan

    Van-Nam Huynh

  3. Artificial Intelligence Group, Engineering Mathematics Department, University of Bristol, BS8 1TR, UK

    Jonathan Lawry

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© 2011 Springer-Verlag Berlin Heidelberg

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Yang, JB., Xu, DL. (2011). Introduction to the ER Rule for Evidence Combination. In: Tang, Y., Huynh, VN., Lawry, J. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2011. Lecture Notes in Computer Science(), vol 7027. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24918-1_2

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  • DOI: https://doi.org/10.1007/978-3-642-24918-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24917-4

  • Online ISBN: 978-3-642-24918-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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