Market demand is highly unpredictable after transportation disruption.
It designs an improved prediction model of grey neural networks.
It determines the number of neurons in the input layer of BP neural networks.
It tests the feasibility of the prediction model through case studies.
It helps optimize inventory and production after transportation disruption.