A DIAGNOSIS SCHEME FOR A LARGE-SCALE SYSTEM

被引：2
|
作者：
LEE, WY [1 ]
ALEXANDER, SM [1 ]
机构：
[1] UNIV LOUISVILLE,DEPT IND ENGN,LOUISVILLE,KY 40292
来源：
JOURNAL OF INTELLIGENT MANUFACTURING | 1993年 / 4卷 / 05期
关键词：
ARTIFICIAL INTELLIGENCE; REASONING PROCESS; ENTROPY; COMPUTER-INTEGRATED MANUFACTURING;
D O I：
10.1007/BF00123779
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a method for diagnosis in a large-scale system environment. The method utilizes the theory of hierarchical systems and hybrid diagnostic reasoning from AI (artificial intelligence). In shallow reasoning, which is a part of hybrid reasoning, the concept of entropy is used to determine which component (that might be responsible for a symptom observed) is to be tested next. The procedure is illustrated using a simulated example of a CIM (computer-integrated manufacturing) system, and is implemented on IntelliCorp's knowledge engineering environment (KEE).
引用
收藏
页码：341 / 354
页数：14
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