【摘要】 提出了一种基于神经网络的工艺设计实例推进索引模型。与现存大多数实例推理系统不同，该方法用神经网络实现实例的动态分类和索引。实例层次分类的三层结构和基于特征的聚类模板概念，为实现基于符号处理的实例推理求解模式向基于神经计算的模式识别求解模式映射提供了条件。该方法的优点在于实例的高速、有效检索，知识获取的简化以及基于神经网络的检索算法的鲁棒性。更多还原

【Abstract】 A new approach to the neural indexing models for case based process planning of turning parts is presented. Unlike most of the existing CBR system, this approach makes use of neural networks to realize the dynamic classfication to index the case. Three levels for hierarchical classfication of cases and a concept of feature based clustering template are presented so as to image the case based reasoning based on symbol processing with the pattern recognition based on neural calculation. This approach makes the neural networks all self orgnized and therefore may reduce periodic human maintenance of the system. Advantages of this approach are the more effective retrieval of the case,the easier knowledge acquisition and the more robust retriever based on neural networks.更多还原