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Sparse Incident-Cluster Learning for 12-hour Port Flood Pre-warning in Digital-Twin Analytics
Port flood digital twins require analytics that warn operators before disruption, but official warning incidents are often few and adjacent observations are temporally dependent. Row-level classification can therefore overstate performance by placing windows from the same event in both model-develop
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