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Fuzzy Optimization Techniques by Hidden Markov Model with Interval Type-2 Fuzzy Parameters

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Abstract

Fuzzy hidden Markov model is the efficient way of finding an optimized path among the states where uncertainty exists. Aggregation operators replaced the conventional operators in the fuzzy environment and play a vital role in real-world problems. Here, the aggregation operators namely trapezoidal interval type-2 weighted arithmetic (TpIT2FFWA) and trapezoidal interval type-2 weighted geometric (TpIT2FFWG) operators have been derived and their desired properties also have been proved based on Frank triangular norms. Using the proposed operators and Viterbi algorithm, decision-making process has been analyzed to choose the best medicine company.

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Author information

Authors and Affiliations

  1. Department of Mathematics, Hindustan Institute of Technology & Science, Chennai, 603 103, India

    D. Nagarajan

  2. Department of Mathematics and Statistics, Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400, Batu Pahat, Malaysia

    J. Kavikumar & M. Lathamaheswari

  3. Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, 50603, Kuala Lumpur, Malaysia

    N. Kumaresan

Authors
  1. D. Nagarajan
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  2. J. Kavikumar
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  3. M. Lathamaheswari
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  4. N. Kumaresan
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Corresponding authors

Correspondence to J. Kavikumar or M. Lathamaheswari.

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Nagarajan, D., Kavikumar, J., Lathamaheswari, M. et al. Fuzzy Optimization Techniques by Hidden Markov Model with Interval Type-2 Fuzzy Parameters. Int. J. Fuzzy Syst. 22, 62–76 (2020). https://doi.org/10.1007/s40815-019-00738-3

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  • DOI: https://doi.org/10.1007/s40815-019-00738-3

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