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predict and rationalise XFEL observables are desperately needed such that XFEL results can reach their full potential. Aim This research aims to utilise the latest advances of computational methods (machine
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial problems
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