Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions

DOI10.1007/978-3-540-75256-1_37zbMath1148.68536OpenAlexW1580762560WikidataQ57657756 ScholiaQ57657756MaRDI QIDQ3524947

Emmanuel Ramasso, M. Rombaut, Denis Pellerin

Publication date: 16 September 2008

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-75256-1_37

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (5)

Bayesian Networks vs. Evidential Networks: An Application to Convoy Detection ⋮ A Solution for the Learning Problem in Evidential (Partially) Hidden Markov Models Based on Conditional Belief Functions and EM ⋮ Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions ⋮ Effectiveness assessment of cyber-physical systems ⋮ A Generalization of the Pignistic Transform for Partial Bet

Cites Work

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• Multisensor triplet Markov chains and theory of evidence
• Belief functions: The disjunctive rule of combination and the generalized Bayesian theorem
• The transferable belief model
• Belief function independence. II: The conditional case.
• Approximating the combination of belief functions using the fast Möbius transform in a coarsened frame.
• Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions
• Symbolic and Quantitative Approaches to Reasoning with Uncertainty
• Symbolic and Quantitative Approaches to Reasoning with Uncertainty

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