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Incomplete Multigranulation Rough Sets in Incomplete Ordered Decision System

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Bio-Inspired Computing and Applications (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

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Abstract

The tolerance relation based incomplete multigranulation rough set is not able to explore the incomplete ordered decision systems. To solve such problem, similarity dominance relation based rough set approach is introduced into multigranulation environment in this paper. Two different types of models: similarity dominance relation based optimistic incomplete multigranulation rough set model and pessimistic incomplete multigranulation rough set model are constructed respectively. The properties and the relationships of them are discussed. Eight types of decision rules in the two models are proposed. An illustrative example is employed.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, NUST, Nanjing, 210094, China

    Li-juan Wang, Xi-bei Yang & Jing-yu Yang

  2. Department of Computer Science and Engineering, JUST, Zhenjiang, 212003, China

    Li-juan Wang, Xi-bei Yang & Chen Wu

Authors
  1. Li-juan Wang
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  2. Xi-bei Yang
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  3. Jing-yu Yang
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  4. Chen Wu
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, 2522, P.O. Box, North Wollongong, NSW, Australia

    Prashan Premaratne

  4. School of Computer Science and Engineering, Inha University, 402-751, Inchon, Korea

    Kyungsook Han

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, Lj., Yang, Xb., Yang, Jy., Wu, C. (2012). Incomplete Multigranulation Rough Sets in Incomplete Ordered Decision System. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_44

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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