Abstract
This chapter presents the scalar approach to intelligent counting. Our main subject will be the concept of the sigma f-count of a fuzzy set. Further, we will extend it to interval-valued fuzzy sets and I-fuzzy sets. Sigma f-counts and their extensions form a formalization of human counting processes under imprecision possibly combined with incompleteness of information. In other words, they offer human-consistent counting procedures. This will be illustrated by a set of examples which refer to the eight-bottle example from Subsection 6.3.4 and show that counting by means of sigma f-counts makes a true practical sense. Those examples can be easily adapted to various problems from the areas of computer science and decision support.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Wygralak, M. (2013). Scalar Approach. In: Intelligent Counting Under Information Imprecision. Studies in Fuzziness and Soft Computing, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34685-9_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-34685-9_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34684-2
Online ISBN: 978-3-642-34685-9
eBook Packages: EngineeringEngineering (R0)