EVALUATIAN OF MEASUREMENT UNCERTAINTY USING THE MONTE CARLO SIMULATION MODELING METHOD

Authors

  • Axmedov Barot Maxmudovich,Karjaubaeva Aynura Iskenderovna Doctor of Technical Sciences, Professor, Head of Department at the Uzbekistan Cadastre Agency/First-year Master's Student, Department of Metrology, Technical Regulation, Standardization, and Certification, Tashkent State Technical University

Keywords:

Measurement uncertainty, Monte Carlo simulation modeling, statistical modeling, measurement model, random variables, sources of uncertainty, result reliability.

Abstract

This article examines the application of the Monte Carlo simulation modeling method for the evaluation of measurement uncertainty. The Monte Carlo simulation approach is presented as an effective method that enables the assessment of uncertainty in measurement results using random variables. The article identifies the primary sources of uncertainty in measurements and describes the stages of the modeling process. Compared to traditional methods, Monte Carlo simulation modeling allows for high-accuracy results while maintaining sensitivity to the complexity of the measurement model and the distribution forms of uncertainties. The findings confirm that this method is an effective tool for improving measurement quality and achieving reliable uncertainty evaluation.

References

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Published

2025-05-24

How to Cite

Axmedov Barot Maxmudovich,Karjaubaeva Aynura Iskenderovna. (2025). EVALUATIAN OF MEASUREMENT UNCERTAINTY USING THE MONTE CARLO SIMULATION MODELING METHOD. Ethiopian International Journal of Multidisciplinary Research, 12(05), 506–511. Retrieved from https://www.eijmr.org/index.php/eijmr/article/view/3131

Issue

Vol. 12 No. 05 (2025): Ethiopian International Journal of Multidisciplinary Research

Section

Articles