Abstract
In Chapter 13, the basic definitions of the fuzzy set theory have been recalled. It is now interesting to see that these definitions can be naturally framed within the mathematical Theory of Evidence , discussed in Part II.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
An important exception to this rule, which represent a limit case of the fuzzy variables, is given by the rectangular membership function, for which all α-cuts are equal.
- 2.
If 11 values are considered, as in (14.1), it is: Xα=0 ≡ A1 ; Xα=0.1 ≡ A2; Xα=0.2 ≡ A3; …;\( X_{\alpha =\alpha _j} \equiv A_i\); …; Xα=1 ≡ A11.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Salicone, S., Prioli, M. (2018). The Relationship Between the Fuzzy Set Theory and the Theory of Evidence. In: Measuring Uncertainty within the Theory of Evidence. Springer Series in Measurement Science and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-74139-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-74139-0_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-74137-6
Online ISBN: 978-3-319-74139-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)