DocumentCode
2005269
Title
Identical foundation of probability theory and fuzzy set theory
Author
De Brucq, Denis ; Colot, Olivier ; Sombo, Arnaud
Author_Institution
PSI, Rouen Univ., Mont Saint Aignan, France
Volume
2
fYear
2002
fDate
8-11 July 2002
Firstpage
1442
Abstract
Information fusion introduces special operators o in probability theory and fuzzy theory. Some serious data certify in each case these two quite distinct techniques. The article shows that four postulates are the unique aim of these two theories. Evidence theory and fuzzy set theory often replace probabilities in medicine, economy and control. Fuzzy theory is used for example in a Japanese photographic engine. We solved the challenge of unifying such different techniques. With the four postulates: noncontradiction, continuity, universality, context dependence, we obtain the same functional equation from which are deduced probability and fuzzy set theories. The same postulates apply to confidences either in the dependence or independence situation. The foundation for the various modern theories of information fusion has been unified in the framework of uncertainty by deductions. The independence between elementary confidences do not need to be understood in the sense of probabilistic meaning.
Keywords
fuzzy set theory; inference mechanisms; probability; sensor fusion; uncertainty handling; Dempster-Shafer; Japanese photographic engine; belief function; context dependence; economy; evidence theory; functional equation; fuzzy set theory; independence situation; information fusion; medicine; probabilistic meaning; probability theory; Calculus; Communication system control; Commutation; Engines; Equations; Fuzzy set theory; Game theory; Graphics; Probability; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2002. Proceedings of the Fifth International Conference on
Conference_Location
Annapolis, MD, USA
Print_ISBN
0-9721844-1-4
Type
conf
DOI
10.1109/ICIF.2002.1020985
Filename
1020985
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