基于粗糙集贝叶斯网络的电子产品设计缺陷评估模型

为了对电子产品设计缺陷进行评估与预测,需要构建电子产品设计缺陷粗糙集数学描述模型。由于电子产品设计缺陷影响因素关系复杂,直接构造贝叶斯网络预测模型困难大、精度差,因此提出一种贝叶斯网络与粗糙集相结合的方法。采用粗糙集来生成贝叶斯网络预测模型的网络结构和各节点的条件概率表,再通过贝叶斯网络的参数估计建立电子产品设计缺陷的预测模型。实际应用证明,该方法简洁有效,可以预测项目可能存在的设计缺陷。

Prediction models of electronic products design defects based on rough set Bayesian network theory

This paper presented an integrated method based on Bayesian network theory and rough set theory to analyze and predict the electronic products design defects. During the process that establishes the relationship among influence factors of electronic products design defects, it is usually difficult to establish directly the Bayesian network prediction model. This paper established the network topology and nodes conditional probability tables by using rough set theory. Then obtained the electronic products design defects prediction model with Bayesian network parameter estimation. At the end of this paper, the Bayesian network model of electronic products design defects, which is proved to be efficiently, is established as well as the learning and reasoning method.