• CN:11-2187/TH
  • ISSN:0577-6686

›› 2004, Vol. 40 ›› Issue (5): 48-52.

• 论文 • 上一篇    下一篇

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CBR诊断系统实例获取的合成相似性度量方法

陈朝阳;张代胜;任佩红   

  1. 合肥工业大学机械与汽车工程学院
  • 发布日期:2004-05-15

SYNTHETIC SIMILARITY MEASURE FOR CASE RETRIEVAL IN CASE-BASED REASONING DIAGNOSIS SYSTEM

Chen Chaoyang;Zhang Daisheng;Ren Peihong   

  1. School of Mechanical and Automotive Engineering, Hefei University of Technology
  • Published:2004-05-15

摘要: 考虑到车辆故障产生的复杂性及系统诊断的特点,采用实例推理诊断方法,而实例推理的关键在于相似实例的获取。针对实例属性存在模糊性的特点,把模糊集概念用于实例的获取中,提出一种实例获取算法——分级合成相似性度量算法,该算法充分考虑到模糊集中心距对实例相似度的影响。最后给出轮胎异常磨损的算法示例,验证了该算法的简洁、合理和有效性。

关键词: 实例获取, 实例推理, 相似性度量, 诊断

Abstract: Case-based reasoning method is presented after analyzing the complexities of vehicle fault and characteristic of diagnosis system. A key issue in case-based reasoning is how to retrieve similar cases. A kind of case retrieval algorithm—multi-layer synthetic similarity measure is preseuted that integrates fuzzy set concepts into the case retrieval process, which focuses fuzzy set center distances influencing on similarity. In the end, an example of abnormal tire wear validates that the algorithm is brief, rational and effective.

Key words: Case retrieval, Case-based reasoning, Diagnosis, Synthetic similarity measure

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