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Measuring Uncertainty for Interval Belief Structures and its Application for Analyzing Weather Forecasts

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 641))

Abstract

While analyzing statistical data we face with a problem of modeling uncertainty. One among well justified models is based on belief structures that allow us to describe imprecision and conflict in information. We use this model for analyzing contradiction in weather forecasts. For this aim we build several measures of contradiction based on the introduced imprecision index and the disjunctive aggregation rule for interval belief structures. We use these characteristics for analyzing weather forecasts.

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Notes

  1. 1.

    Smets considers also in [17] interval belief structures, but they are not finitely defined.

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Correspondence to Andrey G. Bronevich .

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Bronevich, A.G., Spiridenkova, N.S. (2018). Measuring Uncertainty for Interval Belief Structures and its Application for Analyzing Weather Forecasts. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 641. Springer, Cham. https://doi.org/10.1007/978-3-319-66830-7_25

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  • DOI: https://doi.org/10.1007/978-3-319-66830-7_25

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  • Print ISBN: 978-3-319-66829-1

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