Predictability in a Time of Uncertainty: Machine Learning in Logistics
Logistics Viewpoints
JANUARY 21, 2021
ML looks into historical data (for example, transit time statistics of carriers) and data from impactful external factors (such as port congestion, weather or holidays) and uses this information to develop more accurate transit time estimates. The model learns continuously and can adapt to changing conditions in the network.
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