Machine learningEvidential reasoning

Belief Rule Base (RIMER)

Belief Rule Base (BRB), introduced by Yang et al. in 2006 under the RIMER framework, is an expert-system inference methodology that extends classical if-then rules by attaching belief degree distributions to rule consequents. It combines rule-based reasoning with the Evidential Reasoning (ER) approach, enabling the representation and propagation of uncertainty, incompleteness, and vagueness in complex decision problems across engineering, risk assessment, and management domains.

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Sources

  1. Yang, J.-B., Liu, J., Wang, J., Sii, H.-S., & Wang, H.-W. (2006). Belief rule-base inference methodology using the evidential reasoning approach—RIMER. IEEE Transactions on Systems, Man, and Cybernetics—Part A, 36(2), 266–285. DOI: 10.1109/TSMCA.2005.851270

Related methods

ScholarGateBelief Rule Base (Belief Rule-Base Inference (RIMER)). Retrieved 2026-06-04 from https://scholargate.app/tr/soft-computing/belief-rule-base