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Research Papers

How to Take Into Account Model Inaccuracy When Estimating the Uncertainty of the Result of Data Processing

[+] Author and Article Information
Vladik Kreinovich

Cyber-ShARE Center,
University of Texas at El Paso,
El Paso, TX 79968
e-mail: vladik@utep.edu

Olga Kosheleva

Cyber-ShARE Center,
University of Texas at El Paso,
El Paso, TX 79968
e-mail: olgak@utep.edu

Andrzej Pownuk

Cyber-ShARE Center,
University of Texas at El Paso,
El Paso, TX 79968
e-mail: ampownuk@utep.edu

Rodrigo Romero

Cyber-ShARE Center,
University of Texas at El Paso,
El Paso, TX 79968
e-mail: raromero2@utep.edu

1Corresponding author.

Manuscript received January 28, 2016; final manuscript received August 8, 2016; published online November 21, 2016. Assoc. Editor: Athanasios Pantelous.

ASME J. Risk Uncertainty Part B 3(1), 011002 (Nov 21, 2016) (7 pages) Paper No: RISK-16-1040; doi: 10.1115/1.4034450 History: Received January 28, 2016; Accepted August 08, 2016

In engineering design, it is important to guarantee that the values of certain quantities such as stress level, noise level, and vibration level, stay below a certain threshold in all possible situations, i.e., for all possible combinations of the corresponding internal and external parameters. Usually, the number of possible combinations is so large that it is not possible to physically test the system for all these combinations. Instead, we form a computer model of the system and test this model. In this testing, we need to take into account that the computer models are usually approximate. In this paper, we show that the existing techniques for taking model uncertainty into account overestimate the uncertainty of the results. We also show how we can get more accurate estimates.

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