关键词: 供应链柔性, 深度信念网络, BP神经网络, 提升研究

Abstract: To improve supply chain flexibility network for raising the operational efficiency of enterprises,by considering the uncertainty of supply side (node interrupt) and demand side (demand fluctuation) simultaneously,and using the deep belief network that was machine learning model with multiple hidden layers,the model of supply chain flexible network was constructed .Different from the traditional BP neural network,the deep belief network overcame the defects of BP neural network in dealing with the nonlinear relation of complex function.Based on the actual data of a certain manufacturing industry,the contrast analysis showed that the deep belief network was more accurate than the traditional BP neural network.The training time of deep belief network was shorter,and the learning ability was stronger.It could shorten the response time of supply chain network to deal with uncertain risks,which improved the flexibility of the supply chain network.

Key words: supply chain flexibility, deep belief network, BP neural network, enhance research