Enhancing Fault Prediction in Nuclear Industry: Hybridization of Knowledge- and Data-Driven Techniques (Extended Abstract)
Résumé
The present research introduces an approach for predicting faults in nuclear process using data-driven techniques (AI algorithms) augmented with domain-specific knowledge and expertise (such as Rules base models, case based methods or fuzzy methods). We apply our approach to aprocess in the nuclear industry, demonstrating the effectiveness of the framework in accurately predicting failures.
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