Abstract
In this paper a general framework consisting of fuzzy database matching and evidential reasoning is presented. Data is matched onto a database in a fuzzy, i.e. quantified, way. Pieces of evidence are herefrom constructed. These update belief measures connected to the elements of the database, using a simple support belief function. A sorting and grouping of the database elements, and thresholding the beliefs, makes the process stepwise. A qualitative, unambiguous decision support is obtained at every step. The threshold and the maximum belief for a piece of evidence are the parameters varied. Some properties of the framework are examplified in a case study of identifying air targets. For a given ratio of the two parameters, the identification performance shows a surprising non-monotonicity with respect to the threshold.
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Folkesson, M. (2003). Fuzzy Matching and Evidential Reasoning. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45062-7_22
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DOI: https://doi.org/10.1007/978-3-540-45062-7_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40494-1
Online ISBN: 978-3-540-45062-7
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