Learning optimization in simplifying fuzzy rules
Fuzzy Sets and Systems
Redundancy Detection in Semistructured Case Bases
IEEE Transactions on Knowledge and Data Engineering
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Affective factors weight estimation in tree felling time by artificial neural networks
Expert Systems with Applications: An International Journal
A CBR-based fuzzy decision tree approach for database classification
Expert Systems with Applications: An International Journal
Improving generalization of fuzzy IF-THEN rules by maximizing fuzzy entropy
IEEE Transactions on Fuzzy Systems
Adaptive case-based reasoning using retention and forgetting strategies
Knowledge-Based Systems
MRA-based revised CBR model for cost prediction in the early stage of construction projects
Expert Systems with Applications: An International Journal
A knowledge-based system approach for sensor fault modeling, detection and mitigation
Expert Systems with Applications: An International Journal
A comparative study on heuristic algorithms for generating fuzzydecision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Multi-sensor data fusion using support vector machine for motor fault detection
Information Sciences: an International Journal
A rule-based intelligent method for fault diagnosis of rotating machinery
Knowledge-Based Systems
Fuzzy reasoning spiking neural P system for fault diagnosis
Information Sciences: an International Journal
| Hi-index | 0.07 |
For the problem of predicting faults in the status of a shaft furnace, the missed alarm rate and false alarm rate have not been improved significantly by the traditional case-based reasoning (CBR) method. To predict faults more accurately, an improved CBR-based fault prediction method (ICBRP) is proposed in this paper. This ICBRP is composed of a water-filling theory-based weight allocation (WFA) model and a group decision-making-based revision (GDMR) model. According to the optimal allocation mechanism of channel power, a Lagrange function is designed to calculate the weights. Moreover, the credibility of historical results is used to revise the predicted results via the definition of a group utility function. Then, the proposed reasoning strategy can obtain more reasonable weights and take full advantage of comprehensive information from the retrieval results. Finally, the application results indicate that the proposed method is superior to traditional CBR and other methods. This proposed ICBRP significantly reduces the missed alarm rate and the false alarm rate of failure in the furnace status.