Publication detail

# Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertanity of indirect measurements

ŠEDIVÁ, S. HAVLÍKOVÁ, M.

Original Title

Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertanity of indirect measurements

English Title

Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertanity of indirect measurements

Type

conference paper

Language

en

Original Abstract

In this paper the two approaches were used to calculation the uncertainty of the indirect measurements. The relation between standard method for evaluating the measurement uncertainty described in the GUM (the Guide to the Expression of Uncertainty in measurement) and Monte Carlo method is outlined. The Monte Carlo method is numerical procedure for solving mathematical problems by means of simulating random variables. Uncertainty evaluation by Monte Carlo method is based on a probabilistic approach that combines the whole distribution of the factors and is not just based on their means and standard deviation. The results obtain by the Monte Carlo method for the several examples are compared to the corresponding results when the GUM is applied.

English abstract

In this paper the two approaches were used to calculation the uncertainty of the indirect measurements. The relation between standard method for evaluating the measurement uncertainty described in the GUM (the Guide to the Expression of Uncertainty in measurement) and Monte Carlo method is outlined. The Monte Carlo method is numerical procedure for solving mathematical problems by means of simulating random variables. Uncertainty evaluation by Monte Carlo method is based on a probabilistic approach that combines the whole distribution of the factors and is not just based on their means and standard deviation. The results obtain by the Monte Carlo method for the several examples are compared to the corresponding results when the GUM is applied.

Keywords

Measurement uncertainty, Monte Carlo method, indirect measurement, GUM, probability density function

RIV year

2013

Released

26.05.2013

Location

Rytro Poland

ISBN

978-1-4673-4489-0

Book

Proccedings of 14th International Carpathian Control Conference (ICCC)

Pages from

1

Pages to

5

Pages count

5

BibTex

``````
@inproceedings{BUT100301,
author="Soňa {Šedivá} and Marie {Havlíková}",
title="Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect Comparison of GUM and Monte Carlo method for evaluation measurement uncertanity of indirect measurements",
annote="In this paper the two approaches were used to calculation the uncertainty of the indirect measurements. The relation between standard method for evaluating the measurement uncertainty described in the GUM (the Guide to the Expression of Uncertainty in  measurement) and Monte Carlo method is outlined. The Monte Carlo method is numerical procedure for solving mathematical problems by means of simulating random variables. Uncertainty evaluation by Monte Carlo method is based on a probabilistic approach that combines the whole distribution of the factors and is not just based on their means and standard deviation.
The results obtain by the Monte Carlo method for the several examples are compared to the corresponding results when the GUM is applied.",
booktitle="Proccedings of 14th International Carpathian Control Conference (ICCC)",
chapter="100301",
howpublished="electronic, physical medium",
year="2013",
month="may",
pages="1--5",
type="conference paper"
}``````