DocumentCode :
1754864
Title :
The mathematical theory of evidence and measurement uncertainty - Expression and combination of measurement results via the random-fuzzy variables
Author :
Salicone, Simona
Author_Institution :
Dept. of Electron., Inf., & Bioeng, Politec. di Milano, Milan, Italy
Volume :
17
Issue :
5
fYear :
2014
fDate :
Oct. 2014
Firstpage :
36
Lastpage :
44
Abstract :
In a previous paper [1], it was proved how total ignorance can be effectively represented, in Shafer´s theory of evidence [2], by a rectangular possibility distribution. In addition, it was shown how this concept can be usefully employed to mathematically represent situations that are often met in the measurement practice, especially in the industrial world [3]. The aim of this new paper is to show how possibility distributions can be effectively used to represent any kind of knowledge, from total ignorance to total evidence, and combine different contributions, if necessary.
Keywords :
measurement theory; measurement uncertainty; possibility theory; statistical distributions; mathematical theory of evidence; measurement practice; measurement uncertainty; rectangular possibility distribution; Mathematical analysis; Measurement uncertainty; Probability distribution; Systematics;
fLanguage :
English
Journal_Title :
Instrumentation & Measurement Magazine, IEEE
Publisher :
ieee
ISSN :
1094-6969
Type :
jour
DOI :
10.1109/MIM.2014.6912200
Filename :
6912200
Link To Document :
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