Two views of belief: belief as generalized probability and belief as evidence
Artificial Intelligence
Online updating belief rule based system for pipeline leak detection under expert intervention
Expert Systems with Applications: An International Journal
Recursive EM and SAGE-inspired algorithms with application to DOA estimation
IEEE Transactions on Signal Processing - Part I
Belief rule-base inference methodology using the evidential reasoning Approach-RIMER
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A belief-rule-based inventory control method under nonstationary and uncertain demand
Expert Systems with Applications: An International Journal
A novel belief rule base representation, generation and its inference methodology
Knowledge-Based Systems
Construction of a new BRB based model for time series forecasting
Applied Soft Computing
Hi-index | 12.05 |
In this paper a recursive algorithm based on the Bayesian reasoning approach is proposed to update a belief rule based (BRB) expert system for pipeline leak detection and leak size estimation. In addition to using available real time data, expert knowledge on the relationships of the parameters among different rules is incorporated into the updating process so that the performance of the expert system can be improved. Experiments are carried out to compare the newly proposed algorithm with the previously published algorithms, and results show that the proposed algorithm can update the BRB expert system faster and more accurately, which is important for real-time applications. The BRB expert systems can be automatically tuned to represent complex real world systems, and applied widely in engineering.