An improved grey neural network model for predicting transportation disruptions
作者：
Highlights：
• 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.
摘要
•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.
论文关键词：Transportation disruptions,GM(1,1) model,Neural network,Prediction
论文评审过程：Received 25 April 2014, Revised 27 September 2015, Accepted 28 September 2015, Available online 17 October 2015, Version of Record 10 November 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.09.052
