NDLI: Modeling and Processing Measurement Uncertainty Within the Theory of Evidence: Mathematics of Random

Content Provider	IEEE Xplore Digital Library
Author	Ferrero, A. Salicone, S.
Copyright Year	1963
Abstract	Random-fuzzy variables (RFVs) are mathematical variables defined within the theory of evidence. Their importance in measurement activities is due to the fact that they can be employed for the representation of measurement results, together with the associated uncertainty, whether its nature is random effects, systematic effects, or unknown effects. Of course, their importance and usability also depend on the fact that they can be employed for processing measurement results. This paper proposes suitable mathematics and related calculus for processing RFVs, which consider the different nature and the different behavior of the uncertainty effects. The proposed approach yields to process measurement algorithms directly in terms of RFVs so that the final measurement result (and all associated available information) is provided as an RFV
Sponsorship	IEEE Instrumentation and Measurement Society Bureau international des poids et mesures IEEE International Bureau of Weights and Measures (BIPM) URSI NBS Agency Ind. Sci. & Technol., Min. Int. Trade & Ind. Sci. Council Japan International Union of Pure and Applied Physics (IUPAP) NIST NRCC National Conference of Standards Laboratories (NCSL) Allen Osborne Associates Andeen-Hagerling, Inc. Ballantine Lab. Inc. Clarke-Hess Communications Research Corp. Fluke Corporation Guildline Instruments Hewlett-Packard Co. Julie Res. Lab. Inc. Keithley Instruments, Inc. Measurements International Ltd. Canada QuadTech Inc. Quantum Design Inc. Rotek Instrum. Corp. Tegam Inc. Tektronix Inc
Starting Page	704
Ending Page	716
Page Count	13
File Size	804751
File Format	PDF
ISSN	00189456
Volume Number	56
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Measurement uncertainty Mathematics Random variables Calculus Usability Costs Possibility theory unknown contributions Fuzzy averaging operators measurement uncertainty random contributions random–fuzzy variables (RFVs) systematic contributions theory of evidence uncertainty processing
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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