Approximate Inference in Directed Evidential Networks with Conditional Belief Functions Using the Monte Carlo Algorithm

Author:

Laâmari Wafa,Ben Hariz Narjes,Ben Yaghlane Boutheina

Publisher

Springer International Publishing

Reference23 articles.

1. Barnett, J.A.: Computational Methods for a Mathematical Theory of Evidence. In: IJCAI, pp. 868–875 (1981)

2. Ben Yaghlane, B., Mellouli, K.: Inference in Directed Evidential Networks Based on the Transferable Belief Model. IJAR 48(2), 399–418 (2008)

3. Benavoli, A., Ristic, B., Farina, A., Oxenham, M., Chisci, L.: Threat Assessment Using Evidential Networks. Information Fusion, 1–8 (2007)

4. Borgelt, C., Gebhardt, J., Kruse, R.: Possibilistic graphical models. In: International School for the Synthesis of Expert Knowledge, ISSEK (1998)

5. Burger, T., Destercke, D.: How to randomly generate mass functions. Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems 21(5), 645–673 (2013)

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