Abstract
D-S evidence theory has been studied and used for information fusion for a while. Though D-S evidence theory can deal with uncertainty reasoning from imprecise and uncertain information by combining cumulative evidences for changing prior opinions using new evidences. False evidence generated by any fault sensor will result in evidence conflict increasing and inaccurate fused results. Evidence relationship matrix proposed in this paper depicts the relationship among evidences. False evidences can be identified through the analysis of relationships among evidences. Basic probability assignments related to the false evidences may be decreased accordingly. The accuracy of information fusion may be improved. Case studies show the effectiveness of the proposed method.
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© 2006 Springer-Verlag Berlin Heidelberg
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Fan, X., Huang, HZ., Miao, Q. (2006). Evidence Relationship Matrix and Its Application to D-S Evidence Theory for Information Fusion. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_162
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DOI: https://doi.org/10.1007/11875581_162
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
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