Measurement uncertainty evaluation based on quasi Monte-Carlo method

Meifa Huang, Hui Jing, Bing Kuang, Yanru Zhong, Xiangqian Jiang

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


Measurement uncertainty is an important parameter to evaluate the reliability of the measurement results. Because of the limitations of low convergence and unstable results of Monte-Carlo method, quasi Monte-Carlo method is used to estimate the measurement uncertainty. Quasi Monte-Carlo method is an improvement of ordinary Monte Carlo method, which employs highly uniform quasi random numbers to replace Monte Carlo's pseudo random numbers. In the process of evaluation, more homogeneous random numbers or quasi random numbers are first generated based on Halton's sequence. These random numbers are then transformed into the desirable distributed random numbers. A measurement experiment of uncertainty evaluation for the bulk of a cylinder shows that the quasi Monte Carlo method has higher convergence rate and more stable evaluation results than those of Monte-Carlo method. Therefore, the quasi Monte-Carlo method can be applied effectively to evaluate the measurement uncertainty.

Original languageEnglish
Pages (from-to)120-125
Number of pages6
JournalYi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
Issue number1
Publication statusPublished - 2009
Externally publishedYes


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