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