Readings in model-based diagnosis
Readings in model-based diagnosis
C4.5: programs for machine learning
C4.5: programs for machine learning
Applications of machine learning and rule induction
Communications of the ACM
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Guide to Neural Computing Applications
Guide to Neural Computing Applications
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Intelligent Knowledge Based Systems in Electrical Power Engineering
Intelligent Knowledge Based Systems in Electrical Power Engineering
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Analysis of monitored refuelling data is required to confirm that refuelling operations have been correctly completed and that the reactor plant is in a safe condition for continued operation. This paper describes a methodology for identifying key points in the refuelling process thereby providing decision support for post-refuelling analysis. A feature identification technique is described which provides reliable input to Artificial Neural Networks (ANNs) and regression estimation techniques. This technique is shown to be robust against variations in the input data. The analysis in this paper shows that the regression models and ANNs can also provide similarly accurate predictions of a key refuelling event.