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A novel imbalanced fault diagnosis method integrated KLFDA with improved cost-sensitive learning ANBSVM
Xue Jiang, Yuan Xu,
Wei Ke
, Yang Zhang, Qunxiong Zhu, Yanlin He
Faculty of Applied Sciences
Beijing University of Chemical Technology
Ministry of Education of China
National University of Singapore
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引文 斯高帕斯(Scopus)
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Computer Science
Adaptive Learning
100%
fault diagnose method
100%
Discriminant Analysis
100%
Support Vector Machine
100%
Fault Diagnosis
80%
Comparison Result
20%
Minority Class
20%
Overlapping Region
20%
Running Process
20%
Sensitivity Cost
20%
Linear Feature
20%
Majority Class
20%
Simulation Experiment
20%
Diagnostic Accuracy
20%
Objective Function
20%
Negative Effect
20%
Spatial Structure
20%
Mathematics
Bayesian
100%
Discriminant Analysis
100%
Support Vector Machine
100%
Majority Class
20%
Variance
20%
Weight Factor
20%
Objective Function
20%
Nonlinear
20%
Earth and Planetary Sciences
Discriminant Analysis
100%
Support Vector Machine
100%
Flow Pattern
20%
Tennessee
20%
Density Distribution
20%
Chemical Engineering
Support Vector Machine
100%