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Providing support to operators for monitoring safety functions using reinforcement learning
پشتیبانی از اپراتورها برای نظارت بر عملکردهای ایمنی با استفاده از یادگیری تقویتی-2020 Continuous monitoring and diagnosis are important for safe operation of nuclear facilities. In an emergency
shutdown, the diagnostic tasks can be challenging for human operators who may be under intense stress and/or
lack training. In recent years, studies using artificial-intelligence technologies have been actively conducted to
help in diagnostic tasks. The current study proposes a data-driven approach that leverages deep reinforcementlearning
techniques to intelligently learn effective strategies for state diagnosis of safety functions. First, a
learning framework and key elements of reinforcement learning are designed as basic components. Then, a deep
neural-network structure and a deep reinforcement algorithm are presented for diagnosis learning. The experimental
results demonstrate the feasibility of deep reinforcement learning on diagnosing the safety functions
of a nuclear facility. Keywords: Reinforcement learning | Deep neural network | Operator support | Diagnosis | Safety function status check |
مقاله انگلیسی |