Belief rule based expert system for classification problems with new rule activation and weight calculation procedures

Leilei Chang, Zhijie Zhou, Yuan You, Longhao Yang, Zhiguo Zhou

Research output: Contribution to journalArticle

36 Citations (Scopus)

Abstract

Classification problems are significant because they constitute a meta-model for multiple theoretical and practical applications from a wide range of fields. The belief rule based (BRB) expert system has shown potentials in dealing with both quantitative and qualitative information under uncertainty. In this study, a BRB classifier is proposed to solve the classification problem. However, two challenges must be addressed. First, the size of the BRB classifier must be controlled within a feasible range for better expert involvement. Second, the initial parameters of the BRB classifier must be optimized by learning from the experts' knowledge and/or historic data. Therefore, new rule activation and weight calculation procedures are proposed to downsize the BRB classifier while maintaining the matching degree calculation procedure. Moreover, the optimal algorithm using the evidential reasoning (ER) algorithm as the inference engine and the differential evolution (DE) algorithm as the optimization engine is proposed to identify the fittest parameters, including the referenced values of the antecedent attributes, the weights of the rules and the beliefs of the degrees in the conclusion. Five benchmarks, namely, iris, wine, glass, cancer and pima, are studied to validate the efficiency of the proposed BRB classifier. The result shows that all five benchmarks could be precisely modeled with a limited number of rules. The proposed BRB classifier has also shown superior performance in comparing it with the results in the literature.

Original languageEnglish (US)
Pages (from-to)75-91
Number of pages17
JournalInformation Sciences
Volume336
DOIs
StatePublished - Apr 1 2016

Fingerprint

Rule-based Systems
Expert System
Classification Problems
Expert systems
Activation
Classifiers
Chemical activation
Classifier
Inference engines
Wine
Evidential Reasoning
Benchmark
Beliefs
Rule-based
Expert system
Inference Engine
Iris
Differential Evolution Algorithm
Metamodel
Optimal Algorithm

Keywords

  • Belief rule base
  • Classification problems
  • Optimization algorithm

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

Cite this

Belief rule based expert system for classification problems with new rule activation and weight calculation procedures. / Chang, Leilei; Zhou, Zhijie; You, Yuan; Yang, Longhao; Zhou, Zhiguo.

In: Information Sciences, Vol. 336, 01.04.2016, p. 75-91.

Research output: Contribution to journalArticle

Chang, Leilei ; Zhou, Zhijie ; You, Yuan ; Yang, Longhao ; Zhou, Zhiguo. / Belief rule based expert system for classification problems with new rule activation and weight calculation procedures. In: Information Sciences. 2016 ; Vol. 336. pp. 75-91.
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