摘要
事例检索模型直接影响基于事例推理(Case-BasedReasoning,CBR)的结果。该文提出了一种将多概念学习的决策树算法、多维加权贴近度法与模糊综合评判法相结合的事例检索模型,并根据事例状态的属性设计了几种隶属度函数。分析了此模型的优缺点,指出了今后的改进方向。
Case retrieval model directly impacts Case-Based Reasoning(CBR).A case retrieval model is proposed,which combines multi-concept-learning decision tree algorithm and multi-dimension weighted similar degree and fuzzy synthesis evaluation.A few membership functions are advanced by attributes of cases.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第19期77-79,共3页
Computer Engineering and Applications
关键词
基于事例推理
多概念学习的决策树算法
多维加权贴近度
模糊综合评判
Case-Based Reasoning(CBR),multi-concept-learning decision tree algorithm,multi-dimension weighted similar degree,fuzzy synthesis evaluation
