International Journal of Neutrosophic Science

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https://doi.org/10.54216/IJNS

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2690-6805ISSN (Online) 2692-6148ISSN (Print)

Volume 20 , Issue 2 , PP: 27-39, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling

A. M. Mohamed Ibrahim 1 * , Zahid Khan 2 , Fuad S. Al-Duais 3

  • 1 Department of Business Administration, College of Sciences and the Human Sciences in Alaflaj Prince Sattam Bin Abdulaziz University, Saudi Arabia - (am.ibrahim@psau.edu.sa)
  • 2 Department of Mathematics, Hazara University Mansehra, Pakistan - (zahidkhan@hu.edu.pk)
  • 3 Mathematics Department, College of Humanities and Science in Al Aflaj, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia; Business Administration Department, Administrative Science College, Thamar University, Thamar, Yemen - (f.alduais@psau.edu.sa)
  • Doi: https://doi.org/10.54216/IJNS.200203

    Received: November 20, 2022 Accepted: January 17, 2023
    Abstract

    The logistic distribution is widely used to model various types of applied data. The modified logistic distribution under neutrosophic statistics is introduced in this work. The neutrosophic logistic distribution (NLD) and its engineering applications are mainly emphasized. An appealing characteristic of the suggested NLD is that it is useful to many widely utilized survival assessment metrics, including the reliability function, hazard function, and survival function. Applications of some mathematical and statistical properties of the suggested model are discussed. Numerical investigations on simulated data are used to validate the theoretical findings experimentally. From an application point of view, it is inferred that the proposed distribution fits data with imprecise, hazy, and fuzzy information better than the usual model. In addition, the maximum likelihood (ML) technique for the proposed model is discussed under the neutrosophic inference framework. Eventually, some illustrative examples related to system reliability are provided to clarify further the implementation of the neutrosophic probabilistic model in real-world problems.

    Keywords :

    Imprecise data , fuzzy statistics , neutrosophic probability , simulation , maximum likelihood estimation , Reliability

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    Cite This Article As :
    M., A.. , Khan, Zahid. , S., Fuad. A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling. International Journal of Neutrosophic Science, vol. , no. , 2023, pp. 27-39. DOI: https://doi.org/10.54216/IJNS.200203
    M., A. Khan, Z. S., F. (2023). A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling. International Journal of Neutrosophic Science, (), 27-39. DOI: https://doi.org/10.54216/IJNS.200203
    M., A.. Khan, Zahid. S., Fuad. A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling. International Journal of Neutrosophic Science , no. (2023): 27-39. DOI: https://doi.org/10.54216/IJNS.200203
    M., A. , Khan, Z. , S., F. (2023) . A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling. International Journal of Neutrosophic Science , () , 27-39 . DOI: https://doi.org/10.54216/IJNS.200203
    M. A. , Khan Z. , S. F. [2023]. A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling. International Journal of Neutrosophic Science. (): 27-39. DOI: https://doi.org/10.54216/IJNS.200203
    M., A. Khan, Z. S., F. "A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling," International Journal of Neutrosophic Science, vol. , no. , pp. 27-39, 2023. DOI: https://doi.org/10.54216/IJNS.200203