Measuring conflict in evidence theory

Mark J. Wierman

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Conference paper

Measuring conflict in evidence theory

Mark J. Wierman

Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, Vol.3, pp.1741-1745

Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Vancouver, BC, Canada, 07/25/2001 - 07/28/2001)

2001

Abstract

Computer Science(all)

Media Technology

The Shannon entropy measures conflict in probabilistic evidence. Evidence Theory also presents information that is inherently conflicting. Uncertainty measures for conflict in Evidence Theory include aggregate uncertainty, dissonance, confusion, discord, granularity and strife. This paper compares and critiques the properties of these measures.

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Title: Measuring conflict in evidence theory
Creators: Mark J. Wierman (Author) - Department of Computer Science, Design & Journalism
Additional links: Smith, M.H.; Gruver, W.A.; Hall, L.O.
Publication Details: Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, Vol.3, pp.1741-1745
Conference: Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Vancouver, BC, Canada, 07/25/2001 - 07/28/2001)
Series: 3
Number of pages: 5
Identifiers: 991005930570702656
Academic Unit: Computer Science, Design and Journalism
Language: English
Resource Type: Conference paper

Measuring conflict in evidence theory

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