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Fuzzy set methods for uncertainty management in intelligence analysis
Author(s) -
Yager Ronald R.
Publication year - 2006
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.20143
Subject(s) - intelligence analysis , computer science , task (project management) , computational intelligence , set (abstract data type) , fuzzy set , artificial intelligence , fuzzy logic , data mining , operations research , machine learning , mathematics , engineering , computer security , systems engineering , programming language
Considerable concern has arisen regarding the quality of intelligence analysis. This has been, in large part, motivated by the task of determining whether Iraq had weapons of mass destruction. One problem that made this analysis difficult was the uncertainty in much of the information available to the intelligence analysts. In this work, we introduce some tools that can be of use to intelligence analysts for representing and processing uncertain information. We make considerable use of technologies based on fuzzy sets and related disciplines such as approximate reasoning. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 523–544, 2006.