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Digital Twin Data Modelling by Randomized Orthogonal Decomposition and Deep Learning
Associating the dynamical process with a digital twin model of reduced complexity has the significant advantage to map the dynamics with high accuracy and reduced costs in CPU time and hardware to timescales over which that suffers significantly changes and so it is difficult to explore.
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