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Similarity Degree for Multi-Attribute Decision Making with Incomplete Dual Hesitant Fuzzy Sets

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Intelligence Science and Big Data Engineering (IScIDE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10559))

Abstract

Due to the uncertainty and fuzziness of the real world, the dual hesitant fuzzy set (DHFS) has been proposed to express uncertain information during the process of multi-attribute decision making (MADM). In order to process the information with incomplete dual hesitant fuzzy elements (IDHFEs) in MADM, a new similarity degree for MADM with incomplete dual hesitant fuzzy sets (IDHFSs) is proposed. The concept of similarity degree of IDHFEs and similarity aggregation matrix are introduced. Then a complete dual hesitant fuzzy matrix (CDHFM) is obtained by using the maximum similarity to complement the data. An investment selection example is provided to illustrate the validity and applicability of the proposed method.

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Acknowledgments

This work is partially supported by the National Natural Science Foundation of P. R. China (Nos. 61772250, 61673320, 61672127), the Fundamental Research Funds for the Central Universities (No. 2682017ZT12), and the National Natural Science Foundation of Liaoning Province (No. 2015020059).

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Authors and Affiliations

  1. School of Computer and Information Technology, Liaoning Normal University, Dalian, Liaoning, China

    Li Zou

  2. School of Mathematics, Liaoning Normal University, Dalian, Liaoning, China

    Xin Liu, Yuanyuan Shi & Siyuan Luo

Authors
  1. Xin Liu
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  2. Yuanyuan Shi
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  3. Li Zou
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  4. Siyuan Luo
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Corresponding author

Correspondence to Li Zou .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Yi Sun

  2. Dalian University of Technology, Dalian, China

    Huchuan Lu

  3. Dalian University of Technology, Dalian, China

    Lihe Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  5. Beijing Institute of Technology, Beijing, China

    Hua Huang

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Liu, X., Shi, Y., Zou, L., Luo, S. (2017). Similarity Degree for Multi-Attribute Decision Making with Incomplete Dual Hesitant Fuzzy Sets. In: Sun, Y., Lu, H., Zhang, L., Yang, J., Huang, H. (eds) Intelligence Science and Big Data Engineering. IScIDE 2017. Lecture Notes in Computer Science(), vol 10559. Springer, Cham. https://doi.org/10.1007/978-3-319-67777-4_10

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  • DOI: https://doi.org/10.1007/978-3-319-67777-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67776-7

  • Online ISBN: 978-3-319-67777-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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