DocumentCode :
1750707
Title :
Measuring uncertainty and uncertainty-based information for imprecise probabilities
Author :
Klir, George J.
Author_Institution :
Center for Inelligent Syst., State Univ. of New York, Binghamton, NY, USA
Volume :
3
fYear :
2001
fDate :
25-28 July 2001
Firstpage :
1729
Abstract :
After a brief overview of the various theories of imprecise probabilities, the paper focuses on the issue of measuring uncertainty and uncertainty-based information in the individual theories. This issue is covered in three parts. First, essential requirements that must be satisfied by any measure of uncertainty are discussed in generic terms. Next, an overview of established uncertainty measures for the various types of imprecise probabilities is presented. Finally, open problems in this area of research are briefly surveyed
Keywords :
information theory; possibility theory; probability; uncertainty handling; imprecise probabilities; information theory; probability distributions; uncertainty handling; Calculus; Humans; Industrial engineering; Information theory; Intelligent systems; Measurement uncertainty; Probability distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
Type :
conf
DOI :
10.1109/NAFIPS.2001.943813
Filename :
943813
Link To Document :
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