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The machine learning-based effect prediction platform uses the long short-term memory (LSTM) neural network architecture to establish a personalized prediction model by analyzing three categories of historical data (Zhang et al., 2022): 1) training data (including plain and plateau training records, load characteristics, and recovery status)
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