Algorithmic generation of imprecise data from uniform and Weibull distributions
This paper introduced the neutrosophic uniform distribution and innovative simulation methods to generate random numbers from the neutrosophic uniform distribution and the neutrosophic Weibull distribution. We introduced simulation methods and algorithms designed to handle indeterminacy for both of...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2024-04-01
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| Series: | AIMS Mathematics |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2024639?viewType=HTML |
| Summary: | This paper introduced the neutrosophic uniform distribution and innovative simulation methods to generate random numbers from the neutrosophic uniform distribution and the neutrosophic Weibull distribution. We introduced simulation methods and algorithms designed to handle indeterminacy for both of these distributions. We provided random numbers generated from both distributions across a range of parameter values and degrees of indeterminacy. Furthermore, we conducted a comparative analysis between the classical simulation method in classical statistics and the neutrosophic simulation method. Our findings reveal that the proposed neutrosophic simulation method generates random numbers of smaller magnitudes compared to the classical simulation method under classical statistics. This observation forms the basis of our conclusion. |
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| ISSN: | 2473-6988 |