工艺规划决策模型与实例动态归纳  

Process Planning Model and Example Dynamic Generalizing

作　　者：刘长安[1] 查黎敏[1] 

机构地区：[1]山东大学

出　　处：《中国机械工程》2002年第14期1225-1228,共4页China Mechanical Engineering

摘　　要：为解决工艺设计决策过程自动化实现问题 ,基于人工智能的机器学习理论和相似性理论 ,提出了基于 3级工艺规划网络的工艺决策模型和推理策略 ,研究了基于工艺实例的归纳学习方法。与以往的归纳方法不同 ,在预先不确定分类个数和预先不完整的工艺实例集的情况下 ,通过工艺设计过程动态实现归纳和学习。研究了相交度的计算和归纳实现的具体方法。To realize automatic procedure decision-making in process planning, the process planning model and the analogical tactics of a three-layer process planning network are advanced, and the generalizing learning method for process examples is deeply researched, which are based on the machine learning theory of the artificial intelligent theory and the approximate theory. The generalizing method can be applied to the conditions that the group quantity is not defined and the process example collection is not completed. The paper presents the calculation of comparability and the concrete generalizing procedure in detail. The knowledge acquisition system for process planning based on above mentioned theory is also stated.

关 键 词：决策模型 工艺规划 机器学习 动态分类 动态归纳 

分 类 号：TH162[机械工程—机械制造及自动化]