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Measures of assurance and opportunity in modeling uncertain information
Author(s) -
Yager Ronald R.
Publication year - 2012
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21547
Subject(s) - computer science , cardinality (data modeling) , entropy (arrow of time) , set (abstract data type) , information assurance , monotonic function , measure (data warehouse) , representation (politics) , outcome (game theory) , data mining , mathematics , mathematical economics , information security , mathematical analysis , physics , computer security , quantum mechanics , politics , political science , law , programming language
Abstract Our focus is on the representation of uncertain information using set measures. We first discuss the basic properties of monotonic set measures. We then discuss the appropriateness of their use in modeling uncertain information. We look at some notable types of measures of uncertain information and investigate in considerable detail cardinality‐based measures. We look at the Sugeno measure and provide a formulation of the underlying cardinality‐based measures. We then look at quasi‐additive uncertainty measures. We discuss the entropy and attitudinal character of an uncertainty measure. Finally, we introduce the ideas of the assurance and opportunity of the occurrence of an outcome. © 2012 Wiley Periodicals, Inc.