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Complex vague set based concept lattice

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  • Singh, Prem Kumar

Abstract

Recently, the calculus of concept lattice is extended from unipolar to bipolar fuzzy space for precise measurement of vagueness in the attributes based on their acceptation and rejection part. These extensions still unable to highlight the uncertainty in vague attributes and measurement of fluctuation at given phase of time. To conquer this problem, current paper proposed a method for adequate analysis of vagueness and uncertainty in data with fuzzy attributes using the amplitude and phase term of a defined complex vague set based concept lattice. In addition, the analysis derived from the proposed method is compared with CVSS method through an illustrative example.

Suggested Citation

  • Singh, Prem Kumar, 2017. "Complex vague set based concept lattice," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 145-153.
    • Handle: RePEc:eee:chsofr:v:96:y:2017:i:c:p:145-153
    DOI: 10.1016/j.chaos.2017.01.019
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    References listed on IDEAS

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    1. Ch., Aswani Kumar & Dias, Sérgio M. & Vieira, Newton J., 2015. "Knowledge reduction in formal contexts using non-negative matrix factorization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 109(C), pages 46-63.
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    Cited by:

    1. Singh, Prem Kumar, 2018. "Complex neutrosophic concept lattice and its applications to air quality analysis," Chaos, Solitons & Fractals, Elsevier, vol. 109(C), pages 206-213.
    2. Singh, Prem Kumar, 2019. "Vague concept lattice reduction using granular computing and vague entropy," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 165(C), pages 56-73.

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