针对神经网络和专家系统相结合的知识利用不充分问题,提出了一种神经网络专家系统模型,通过在神经网络与专家系统各自的知识库之间设计筛选器结构,在专家系统更新知识后对神经网络接收的诊断数据进行判断,对于诊断中调用了新知识的数据,将其作为样本参与神经网络的训练,以此完成神经网络对规则类知识的获取,实现了两种异构系统间的知识传递,增加了知识的利用效率。 Aiming at the problem of insufficient use of knowledge combined with neural network and expert system, a neural network expert system model is proposed. By designing the filter structure between the neural network and the expert system, Neural network to determine the diagnostic data received for the diagnosis of the transfer of new knowledge of the data as a sample to participate in the training of the neural network to complete the neural network rules of knowledge acquisition to achieve the two kinds of heterogeneous systems Knowledge transfer, increasing the efficiency of the use of knowledge.