Revolutionizing Nuclear Safety: Hybrid Tech Unveiled!
Enhancing failure prediction in the nuclear industry requires innovative approaches that combine the strengths of both knowledge-driven and data-driven techniques. This hybrid methodology leverages expert domain knowledge, engineering principles, and historical failure data alongside advanced machine learning and AI models. By integrating these approaches, nuclear facilities can achieve more accurate predictions, early detection of potential failures, and improved system reliability. This research highlights the importance of predictive maintenance, risk assessment, and safety optimization in nuclear power plants, ultimately contributing to higher operational efficiency and enhanced safety standards.
8th Edition of Applied Scientist Awards | 26-27 September 2025 | Mumbai, India
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