Dynamic Rule Activation Method Based on Activation Factor for Extended Belief Rule-based Systems

Tian-Yu Ren, Fei-Fei Ye, Long-Hao Yang, Jun Liu, Yanyan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Extended belief rule-based system (EBRBS) as an integrated data and knowledge driven rule-based system has attracted much attention in the last few years and has been widely used in classification problems. Data inconsistency and data incompleteness are two common issues and result in the decrease of the accuracy of data-driven model including EBRBS. Although a dynamic rule activation (DRA) method was proposed to solve these two issues by selecting the most consistent rules and has shown its capability in improving the performance of EBRBS, there still exists some drawbacks in its efficiency and rationality. Hence, a new DRA method based on activation factor (called AFDRA) is proposed for EBRBS to better handle the data inconsistency and data incompleteness issues. Case studies show that the AFDRA method not only has a great improvement in the term of efficiency over the DRA method, but also achieves better performance for EBRBS in classification problems.
Original languageEnglish
Title of host publication2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
PublisherIEEE
Pages82-86
Number of pages5
ISBN (Electronic)978-1-6654-0553-9, 978-1-6654-0552-2
ISBN (Print)978-1-6654-0554-6
DOIs
Publication statusPublished (in print/issue) - 18 Apr 2022
Event16th International Conference on Intelligent Systems and Knowledge Engineering - Chengdu, China
Duration: 26 Nov 202128 Nov 2021

Publication series

Name2021 IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021

Conference

Conference16th International Conference on Intelligent Systems and Knowledge Engineering
Abbreviated titleISKE
Country/TerritoryChina
CityChengdu
Period26/11/2128/11/21

Bibliographical note

Funding Information:
This research was supported by the National Natural Science Foundation of China (Nos. 72001043 and 71872047), the Natural Science Foundation of Fujian Province of China (No. 2020J05122), the Humanities and Social Science Foundation of the Ministry of Education of China (Nos. 20YJC630188 and 19YJC630022), the Social Science Planning Fund Project of Fujian Province of China (No. FJ2019C032).

Publisher Copyright:
© 2021 IEEE.

Keywords

  • activation factor
  • dynamic rule activation
  • extended belief rule based system
  • incompleteness
  • inconsistency

Fingerprint

Dive into the research topics of 'Dynamic Rule Activation Method Based on Activation Factor for Extended Belief Rule-based Systems'. Together they form a unique fingerprint.

Cite this