Abstract: This article sets up a supply chain performance prediction model based on rough sets and neural network from Knowledge Discovery and Data Mining perspective,gives a supply chain performance prediction example,firstly reduces its index based on the balanced scorecard system,then inputs the reduction index to BP neural network for intelligent training,Finally,inputs the forecast sample to the trained network BP and gets supply chain performance predictive value.The forecast result is matched with the actual result.

Key words: rough sets, BP neural network, reduction, discernable matrix, supply chain performance prediction model

摘要： 文章从知识发现和数据挖掘的角度,利用粗糙集和BP神经网络的理论和方法,建立了基于粗糙集和BP神经网络相结合的供应链绩效预测模型。并结合一个供应链绩效预测实例,首先对其基于平衡记分卡的指标体系进行了约简,然后将约简的评价指标输入到BP神经网络中进行智能训练,最后把预测的样本输入到训练好的BP网络中得出供应链绩效的预测值,预测结果与实际结果基本吻合。

关键词: 粗糙集, BP神经网络, 约简, 分辨矩阵, 供应链绩效预测模型