DocumentCode :
467724
Title :
Research on Evaluation Method Based on Multi-Hierarchy Grey Correlative Analysis in Intelligent Fault Diagnosis
Author :
Cao, Shou-qi ; Han, Yan-ling
Author_Institution :
Shanghai Fisheries Univ., Shanghai
Volume :
2
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
962
Lastpage :
967
Abstract :
Diagnosis decision-making and evaluation analysis is two closely-related contents in the process of intelligent fault diagnosis, correct decision-making could be made only based on objective and fair evaluation. This paper gave the evaluation indicator architecture for intelligent fault diagnosis decision-making; combining the special superiority of grey correlative analysis in the way of quantify analysis and evaluation for nonlinear, dispersion, and dynamic date, associated the grey correlative analysis with hierarchical analysis method, brought forward the evaluation method based on multi-hierarchy grey correlative analysis and applied it into intelligent fault diagnosis, researched deeply its principle, algorithm and evaluation execution process, and finally gave analysis sample. By integrating estimation into the decision-making process of intelligent diagnosis, provides the strong support in the way of analysis method for the correct decision-making of intelligent fault diagnosis.
Keywords :
artificial intelligence; decision making; fault diagnosis; diagnosis decision-making; evaluation indicator architecture; hierarchical analysis method; intelligent fault diagnosis; multi-hierarchy grey correlative analysis; Algorithm design and analysis; Cybernetics; Decision making; Educational institutions; Fault diagnosis; Information analysis; Large-scale systems; Learning systems; Machine learning; Production; Evaluation Architecture; Intelligent Fault Diagnosis; Multi-hierarchy Grey Correlative Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370281
Filename :
4370281
Link To Document :
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