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Comparative analysis of covering based soft rough sets and multi-layered fuzzy attributed fuzzy soft matrices

Author

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  • P. Miya Fathima Benazir

    (SIMATS)

  • G. Gomathi

    (SIMATS)

Abstract

The aim of this study is to introduce an algorithm that enhances the accuracy of decision-making by ranking the attributes. In addition, we analysis and exploit covering based soft rough sets and multilayered fuzzy attributed fuzzy soft matrices notions to creates an algorithm that can handle intricate scenarios involving decision making. These approaches are used to evaluate consumer satisfactions level in the E-commerce domain, which helps businesses optimise results by empowering them to make well-informed decisions and adjust their strategies in the face of a constantly changing E-commerce environment.

Suggested Citation

  • P. Miya Fathima Benazir & G. Gomathi, 2024. "Comparative analysis of covering based soft rough sets and multi-layered fuzzy attributed fuzzy soft matrices," OPSEARCH, Springer;Operational Research Society of India, vol. 61(4), pages 2055-2071, December.
    • Handle: RePEc:spr:opsear:v:61:y:2024:i:4:d:10.1007_s12597-024-00764-2
    DOI: 10.1007/s12597-024-00764-2
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    References listed on IDEAS

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    1. Matthias Ehrgott, 2005. "Multicriteria Optimization," Springer Books, Springer, edition 0, number 978-3-540-27659-3, March.
    2. B. Praba & G. Gomathi & Vijaya Mani, 2020. "Twin approximation space and its application in analysing employee engagement and employee value proposition," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 12(4), pages 299-308.
    3. Xiaolu Wang & Christer Carlsson, 2016. "Patent-related decision-making with fuzzy real option analysis," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 9(4), pages 467-486.
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