Dynamic case based reasoning in fault diagnosis and prognosis

被引：0
|
作者：
Berenji, H [1 ]
Wang, Y [1 ]
Saxena, A [1 ]
机构：
[1] NASA, Intelligent Inference Syst Corp, Moffett Field, CA 94035 USA
来源：
FUZZ-IEEE 2005: Proceedings of the IEEE International Conference on Fuzzy Systems: BIGGEST LITTLE CONFERENCE IN THE WORLD | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Dynamic Case Based Reasoning (DCBR) is a powerful technique for Fault Diagnosis and Prognosis. DCBR allows the accumulation of experience from inclusion of the new cases and therefore accommodates learning. In this paper, we discuss DCBR and develop a methodology for using it in a dynamic model of a chiller system.
引用
收藏
页码：845 / 850
页数：6
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