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Volume 7, Issue 2
Characterization of Distributions Through Stochastic Models Under Fuzzy Random Variables

D. Vijayabalan, M.L. Suresh, G. Kuppuswami, T. Vivekanandan, K. Kavitha & S. Geethamalini

DOI: 10.12150/jnma.2025.649

J. Nonl. Mod. Anal., 7 (2025), pp. 649-665.

Published online: 2025-04

[An open-access article; the PDF is free to any online user.]

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  • Abstract

This paper is noteworthy because it investigates a novel method for comparing the expectations of stochastic models in fuzzy contexts. Actuarial science and economics both depend on stochastic models. Understanding the novel concepts of stochastic comparison of stochastic models based on the exponential order is the main advantage of this study. We solved the preservation properties and theorem, created a new definition, and put the fuzzy mean inactive time order definition into practice. Stochastic models are handled in a variety of applications.

  • Keywords

Fuzzy set, random variables, stochastic orders.

  • AMS Subject Headings

35A01, 65L10, 65L12

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JNMA-7-649, author = {Vijayabalan , D.Suresh , M.L.Kuppuswami , G.Vivekanandan , T.Kavitha , K. and Geethamalini , S.}, title = {Characterization of Distributions Through Stochastic Models Under Fuzzy Random Variables}, journal = {Journal of Nonlinear Modeling and Analysis}, year = {2025}, volume = {7}, number = {2}, pages = {649--665}, abstract = {

This paper is noteworthy because it investigates a novel method for comparing the expectations of stochastic models in fuzzy contexts. Actuarial science and economics both depend on stochastic models. Understanding the novel concepts of stochastic comparison of stochastic models based on the exponential order is the main advantage of this study. We solved the preservation properties and theorem, created a new definition, and put the fuzzy mean inactive time order definition into practice. Stochastic models are handled in a variety of applications.

}, issn = {2562-2862}, doi = {https://doi.org/10.12150/jnma.2025.649}, url = {http://global-sci.org/intro/article_detail/jnma/24020.html} }
TY - JOUR T1 - Characterization of Distributions Through Stochastic Models Under Fuzzy Random Variables AU - Vijayabalan , D. AU - Suresh , M.L. AU - Kuppuswami , G. AU - Vivekanandan , T. AU - Kavitha , K. AU - Geethamalini , S. JO - Journal of Nonlinear Modeling and Analysis VL - 2 SP - 649 EP - 665 PY - 2025 DA - 2025/04 SN - 7 DO - http://doi.org/10.12150/jnma.2025.649 UR - https://global-sci.org/intro/article_detail/jnma/24020.html KW - Fuzzy set, random variables, stochastic orders. AB -

This paper is noteworthy because it investigates a novel method for comparing the expectations of stochastic models in fuzzy contexts. Actuarial science and economics both depend on stochastic models. Understanding the novel concepts of stochastic comparison of stochastic models based on the exponential order is the main advantage of this study. We solved the preservation properties and theorem, created a new definition, and put the fuzzy mean inactive time order definition into practice. Stochastic models are handled in a variety of applications.

Vijayabalan , D.Suresh , M.L.Kuppuswami , G.Vivekanandan , T.Kavitha , K. and Geethamalini , S.. (2025). Characterization of Distributions Through Stochastic Models Under Fuzzy Random Variables. Journal of Nonlinear Modeling and Analysis. 7 (2). 649-665. doi:10.12150/jnma.2025.649
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