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Generalized Dominance-Based Rough Set Model for the Dominance Intuitionistic Fuzzy Information Systems

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Rough Sets and Knowledge Technology (RSKT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8818))

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Abstract

A dominance-based rough set approach was proposed by replacing the indiscernibility relation with a dominance relation. The aim of this paper is to present a new extension of the dominance-based rough set by means of defining a new dominance relation, i.e., generalized dominance-based rough set model is proposed based on the dominance intuitionistic fuzzy information systems. To get the optimal decision rules from the existing dominance intuitionistic fuzzy information systems, a lower and upper approximation reduction and rule extraction algorithm are investigated. Furthermore, several properties of the generalized dominance-based rough set model are given, and the relationships between this model and the others dominance-based rough set models are also examined.

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Author information

Authors and Affiliations

  1. School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China

    Xiaoxia Zhang & Degang Chen

Authors
  1. Xiaoxia Zhang
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  2. Degang Chen
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Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    Duoqian Miao

  2. Department of Electrical and Computer En, University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

  3. University of Warsaw, Warsaw, Poland

    Dominik Ślȩzak

  4. University of Applied Sciences, München, Germany

    Georg Peters

  5. Tianjin University, Tianjin, China

    Qinghua Hu

  6. Tongji University, Shanghai, China

    Ruizhi Wang

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© 2014 Springer International Publishing Switzerland

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Zhang, X., Chen, D. (2014). Generalized Dominance-Based Rough Set Model for the Dominance Intuitionistic Fuzzy Information Systems. In: Miao, D., Pedrycz, W., Ślȩzak, D., Peters, G., Hu, Q., Wang, R. (eds) Rough Sets and Knowledge Technology. RSKT 2014. Lecture Notes in Computer Science(), vol 8818. Springer, Cham. https://doi.org/10.1007/978-3-319-11740-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-11740-9_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11739-3

  • Online ISBN: 978-3-319-11740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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