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Possibility Vague Soft Expert Set Theory and Its Application in Decision Making

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Soft Computing in Data Science (SCDS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 545))

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Abstract

In this paper, we aim to extend the notion of classical soft expert sets to possibility vague soft expert sets by applying the theory of soft expert sets to possibility vague soft sets. The complement, union, intersection, AND and OR operations as well as some related concepts pertaining to this notion are defined. The algebraic properties such as the De Morgan’s laws and the relevant laws of possibility vague soft expert sets are studied and subsequently proved. Lastly, this concept are applied to a decision making problem and its effectiveness is demonstrated using a hypothetical example.

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Author information

Authors and Affiliations

  1. Department of Actuarial Science and Applied Statistics, Faculty of Business and Information Science, UCSI University, Jalan Menara Gading, 56000, Cheras, Kuala Lumpur, Malaysia

    Ganeshsree Selvachandran

  2. School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Selangor DE, Malaysia

    Abdul Razak Salleh

Authors
  1. Ganeshsree Selvachandran
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  2. Abdul Razak Salleh
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Corresponding author

Correspondence to Ganeshsree Selvachandran .

Editor information

Editors and Affiliations

  1. University of Tennessee, Knoxville, Tennessee, USA

    Michael W. Berry

  2. Universiti Teknologi MARA, Shah Alam, Malaysia

    Azlinah Mohamed

  3. Universiti Teknologi MARA, Shah Alam, Malaysia

    Bee Wah Yap

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© 2015 Springer Science+Business Media Singapore

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Selvachandran, G., Salleh, A.R. (2015). Possibility Vague Soft Expert Set Theory and Its Application in Decision Making. In: Berry, M., Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2015. Communications in Computer and Information Science, vol 545. Springer, Singapore. https://doi.org/10.1007/978-981-287-936-3_8

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  • DOI: https://doi.org/10.1007/978-981-287-936-3_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-287-935-6

  • Online ISBN: 978-981-287-936-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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