Designing Possibilistic Information Fusion—The Importance of Associativity, Consistency, and Redundancy
نویسندگان
چکیده
One of the main challenges in designing information fusion systems is to decide on structure and order which aggregated. The key criteria by topologies are constructed include associativity rules as well consistency redundancy sources. Fusion regarding these flexible design, produce maximal specific information, robust against unreliable or defective In this article, an automated data-driven design approach for possibilistic detailed that explicitly considers associativity, consistency, redundancy. proposed intended handle epistemic uncertainty—that is, result even case lacking training data. evaluated selected publicly available real-world datasets obtained from technical systems. Epistemic uncertainty simulated withholding parts It shown that, context, sole criterion results not robust. Including a metric leads improved robustness uncertainty.
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ژورنال
عنوان ژورنال: Metrology
سال: 2022
ISSN: ['2673-8244']
DOI: https://doi.org/10.3390/metrology2020012