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Interval Valued Hesitant Fuzzy Soft Sets and Its Application in Stock Market Analysis

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 517))

Abstract

Molodtsov introduced soft set theory in 1999 to handle uncertainty. It has been found that hybrid models are more useful than that of individual components. Yang et al. introduced the concept of interval valued fuzzy soft set (IVFSS) by combining the interval valued fuzzy sets (IVFS) and soft set model. In this paper we extend it by introducing interval valued hesitant fuzzy soft sets (IVHFSS) through the membership function approach introduced by Tripathy et al. in 2015. To illustrate the application of the new model, we provide a decision making algorithm and use it in stock market analysis,

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Authors and Affiliations

  1. School of Computer Science and Engineering, VIT University, Vellore, Tamil Nadu, India

    T. R. Sooraj & B. K. Tripathy

Authors
  1. T. R. Sooraj
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  2. B. K. Tripathy
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Corresponding author

Correspondence to T. R. Sooraj .

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Editors and Affiliations

  1. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    K. Vijayakumar

  3. Department of Electrical and Electronics Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Sooraj, T.R., Tripathy, B.K. (2017). Interval Valued Hesitant Fuzzy Soft Sets and Its Application in Stock Market Analysis. In: Dash, S., Vijayakumar, K., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-10-3174-8_63

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  • DOI: https://doi.org/10.1007/978-981-10-3174-8_63

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3173-1

  • Online ISBN: 978-981-10-3174-8

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