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- W2377029904 abstract "A fault diagnosis algorithm based on Boosting and support vector machines for aero-engine was proposed.The algorithm adopts support vector machine(SVM) with linear kernel as weak learners and use Boosting algorithm to generate a set of weak learners and then fuse all the learners via weighting.The algorithm both possesses the virtue of SVM and Boosting,which separately shows strong classification ability and superiority for imbalanced datasets.To validate the efficiency of the new algorithm,the typical bearing faults,the main deduction gear faults,and the oil system faults were investigated via real inspection data.In order to reduce the redundancy of the features,principal component analysis(PCA) and rough set theory(RST) were used to determine the richest features.Then,a Boosting-SVM classifier was build using the training data.Results towards the testing data show that the proposed Boosting-SVM algorithm gives a better average success rate than standard SVM,which is significantly improved from 79.4% to 85.7%." @default.
- W2377029904 created "2016-06-24" @default.
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- W2377029904 date "2010-01-01" @default.
- W2377029904 modified "2023-10-03" @default.
- W2377029904 title "Aero-engine fault diagnosis based on Boosting-SVM" @default.
- W2377029904 hasPublicationYear "2010" @default.
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