Belief rule-base expert system with multilayer tree structure for complex problems modeling

Longhao Yang, Feifei Ye, J. Liu, Yingming Wang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
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Belief rule-base (BRB) expert system is one of recognized and fast-growing approaches in the areas of complex problems modeling. However, the conventional BRB has to suffer from the combinatorial explosion problem since the number of rules in BRB expands exponentially with the number of attributes in complex problems, although many alternative techniques have been looked at with the purpose of downsizing BRB. Motivated by this challenge, in this paper, multilayer tree structure (MTS) is introduced for the first time to define hierarchical BRB, also known as MTS-BRB. MTS- BRB is able to overcome the combinatorial explosion problem of the conventional BRB. Thereafter, the additional modeling, inferencing, and learning procedures are proposed to create a self-organized MTS-BRB expert system. To demonstrate the development process and benefits of the MTS-BRB expert system, case studies including benchmark classification datasets and research and development (R&D) project risk assessment have been done. The comparative results showed that, in terms of modelling effectiveness and/or prediction accuracy, MTS-BRB expert system surpasses various existing, as well as traditional fuzzy system-related and machine learning-related methodologies
Original languageEnglish
Article number119567
JournalExpert Systems with Applications
Early online date19 Jan 2023
Publication statusPublished (in print/issue) - 1 May 2023

Bibliographical note

Funding Information:
This research was supported by the National Natural Science Foundation of China (Nos. 72001043, 61773123, and 72001042), the Humanities and Social Science Foundation of the Ministry of Education of China (No. 20YJC630188), and the National Science Foundation of Fujian Province of China (Nos. 2020J05122 and 2022J01178).

Publisher Copyright:
© 2023 Elsevier Ltd


  • Belief rule base
  • Multilayer tree structure
  • Expert system
  • Complex problems
  • Combinatorial explosion problem


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