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A Framework of Decision Making Based on Maximal Supported Sets

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Advances in Neural Networks - ISNN 2010 (ISNN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6063))

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Abstract

In this paper, we present an alternative technique of decision making through parameterization reduction by determining maximal supported sets from a Boolean-valued information system based soft set theory. Based on such reduction, the maximal support will be calculated to determine the optimal choice. It is shown that the technique is identical to normal parameter reduction from previous research on soft set for decision making. While maximal support reduction is in fact has also provided consistency choices in decision making.

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References

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Author information

Authors and Affiliations

  1. Faculty of Informatics, Universiti Darul Iman Malaysia, Terengganu, Malaysia

    Ahmad Nazari Mohd Rose

  2. Department of Mathematics Education, Universitas Ahmad Dahlan, Indonesia

    Tutut Herawan

  3. FTMM, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Mustafa Mat Deris

Authors
  1. Ahmad Nazari Mohd Rose
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  2. Tutut Herawan
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  3. Mustafa Mat Deris
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China

    Liqing Zhang

  2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800, Dongchuan Road, 200240, Shanghai, China

    Bao-Liang Lu

  3. Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water bay, Kowloon, Hong Kong, China

    James Kwok

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© 2010 Springer-Verlag Berlin Heidelberg

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Mohd Rose, A.N., Herawan, T., Mat Deris, M. (2010). A Framework of Decision Making Based on Maximal Supported Sets. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13278-0_61

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  • DOI: https://doi.org/10.1007/978-3-642-13278-0_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13277-3

  • Online ISBN: 978-3-642-13278-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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