【摘要】 论文提出了在大型数据库中,为飞行器故障诊断的KDD故障诊断树和知识演变模式。其思想是在飞行器工程领域中,创建故障诊断树和基于知识演变的系统。这种知识演变模式提供了同步和交互进行的两种处理模式:数据挖掘处理和优化处理。在基于知识演变模式中,数据挖掘处理在信念空间层进行符号推理,而优化处理在整体空间层进行查询。这些模式和故障诊断树都是为快速查找飞行器故障服务的,可以有效地提高飞行器试验的成功率。更多还原

【Abstract】 In this paper,the authors proposes a failure diagnostic tree and knowledge evolutionary patterns for the vehi-cle’s failure diagnosis using KDD in large scale databases.The idea here is to construct a failure diagnostic tree and knowledge-based evolutionary systems that are applied in the Vehicle Engineering Domain.This patterns provides possi-bility of making two processes,the data mining process and optimization processes,work simultaneously and reciprocally.Based on knowledge evolutionary patterns,the data mining process is supported by symbolic reasoning in the belief space,and the optimization process is supported by evolutionary search in the population space.These patterns and fail-ure diagnostic tree both have served a search Vehicle failure quickly,could made a success of Vehicle experiment on it effectively in practical.更多还原