Uncertainty-driven generation of neutrosophic random variates from the Weibull distribution
Abstract Objective This paper aims to introduce an algorithm designed for generating random variates in situations characterized by uncertainty. Method The paper outlines the development of two distinct algorithms for producing both minimum and maximum neutrosophic data based on the Weibull distribu...
I tiakina i:
| Kaituhi matua: | |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
SpringerOpen
2023-12-01
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| Rangatū: | Journal of Big Data |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1186/s40537-023-00860-y |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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