Joint treatment of imprecision and randomness in uncertainty propagation

This paper presents and studies in detail a hybrid method of uncertainty propagation for the case where knowledge regarding some parameters of a physical model is represented by probability measures, while others are represented by possibility measures or belief functions.

Mots clés

Fuzzy numbers Probability Possibility Belief functions Dependence

Domaines

Intelligence artificielle [cs.AI]

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https://hal.inrae.fr/hal-02818905

Soumis le : samedi 6 juin 2020-16:15:18

Dernière modification le : vendredi 26 avril 2024-09:08:03

Dates et versions

hal-02818905 , version 1 (06-06-2020)

Identifiants

HAL Id : hal-02818905 , version 1
DOI : 10.1016/B978-044452075-3/50004-2
PRODINRA : 479458

Citer

Cédric Baudrit, Didier Dubois, Dominique Guyonnet, Hélène Fargier. Joint treatment of imprecision and randomness in uncertainty propagation. Bernadette Bouchon-Meunier; Giulianella Coletti; Ronald Yage. Modern Information Processing : From Theory to Applications, Elsevier Science, pp.37-47, 2006, 978-0-444-52075-3. ⟨10.1016/B978-044452075-3/50004-2⟩. ⟨hal-02818905⟩

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