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Applications of Plausible, Paradoxical, and Neutrosophical Reasoning for Information Fusion (The Sixth International Conference on Information Fusion)
July 8-11, 2003
Radison Plaza Hotel at the Pier
Cairns, Queensland, Australia

Organizers
Chair: Dr. Jean Dezert, Co-Chair: Dr. Florentin Smarandache; Sponsors: Fusion 2003 Organizers, ONERA (France), University of New Mexico (USA)

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Equivalence Between Belief Theories and Naive Bayesian Fusion for Systems with Independent Evidential Data : Part I The Theory
by
John Sudano
Lockheed Martin, Moorestown, NJ, 08057, USA

The process of fusing multiple independent sensor measurements, communication link data from other independent systems, and dynamic data base information is essential to support critical decisions in a timely way. Many real systems can be mapped to such a process. The independence of the input evidential data with an equal probable uniform prior probability distribution (i.e. Naive Bayesian fusion) greatly simplifies the mathematical techniques used to properly fuse the evidential data. Equivalence between Belief Fusion and Naive Bayesian is shown for this process. The equivalence comparison is done in probability space. A title of a 2001 colloquium "Data Fusion & Target ID: Dempster-Shafer & Probability Theories Holy War" depicts the state of mind of many researchers. The goal of this paper is to show that large areas from both mathematical camps are equivalent.

Date received: February 19, 2003

Copyright © 2003 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cajx-11.