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Interval-Valued Fuzzy Reasoning Based on Weighted Similarity Measure

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Fuzzy Information and Engineering Volume 2

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 62))

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Abstract

This paper presents a method of bidirectional interval-valued fuzzy approximate reasoning by employing a weighted similarity measure between the fact and the antecedent(or consequent) portion of interval-valued fuzzy production rule. Our proposed method is more reasonable and flexible than the one presented in the paper by Chen [Fuzzy Sets and Systems, 91(1997)339-353] due to the fact that it not only can deal with multidimensional interval-valued fuzzy reasoning scheme, but also consider the different importance degree of linguistic variables in production rule and that of elements in each universe. One numerical example is given to illustrate the efficiency and feasibility of the proposed new method.

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Author information

Authors and Affiliations

  1. School of Information Science, Guangdong University of Foreign Studies, Guangzhou, 510420, China

    Qian-sheng Zhang & Bi Li

Authors
  1. Qian-sheng Zhang
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  2. Bi Li
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Editor information

Editors and Affiliations

  1. Guangzhou University, China

    Bingyuan Cao

  2. Chongqing University of Science and Technology, Chongqing, PR China

    Tai-Fu Li

  3. Hainan Normal University, Hainan, PR China

    Cheng-Yi Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhang, Qs., Li, B. (2009). Interval-Valued Fuzzy Reasoning Based on Weighted Similarity Measure. In: Cao, B., Li, TF., Zhang, CY. (eds) Fuzzy Information and Engineering Volume 2. Advances in Intelligent and Soft Computing, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03664-4_155

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  • DOI: https://doi.org/10.1007/978-3-642-03664-4_155

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03663-7

  • Online ISBN: 978-3-642-03664-4

  • eBook Packages: EngineeringEngineering (R0)

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