New activation weight calculation and parameter optimisation for extended belief rule-based system based on sensitivity analysis

Longhao Yang, J. Liu, Yingming Wang, Luis Martinez

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)
195 Downloads (Pure)

Abstract

An extended belief rule-based (EBRB) system is superior to existing rule-based systems in managing several types of uncertain information and modeling complex issues effectively and efficiently. However, the accuracy and interpretability of the EBRB system still need to be enhanced by addressing the following shortcomings: the interpretability of the intermediate variables in the EBRB system should be definite and the system parameters must be effectively determined. Therefore, we distinguish discrete and continuous data types to perform sensitivity analysis twice: first, on the rule inference scheme to study the interpretability of individual matching degrees and activation weights; and second, on the rule generation scheme to examine the effect of utility values and attribute weights on the accuracy of the EBRB system. Based on the analyses, we propose a novel activation weight calculation method and parameter optimization method to enhance the interpretability and accuracy of the EBRB system, respectively. We then present three case studies to elucidate the effectiveness of the proposed methods. The results indicate that the enhanced EBRB system prevents counterintuitive and insensitive situations and obtains better accuracies than some studies.
Original languageEnglish
Pages (from-to)837–878
Number of pages42
JournalKnowledge and Information Systems
Volume60
Early online date22 May 2018
DOIs
Publication statusPublished (in print/issue) - 1 Aug 2019

Keywords

  • Extended belief rule-based system
  • Activation weight calculation
  • Parameter optimization
  • Interpretability
  • Accuracy

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