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- W2367778106 abstract "Aiming at the coupling relationship among electronic equipment’s feature parameters,a hybrid Support Vector Regression(SVR) based fault prediction model is proposed in the paper,both the time relativity and space relativity of the feature parameter are taken into account,and it designes the algorithm process of hybrid SVR which improves the prediction accuracy by fusing the vertical historical state data and the horizontal correlation parameter together,applying D-S evidence theory.Experimental results show that,compared with vertical SVR or horizontal SVR,the proposed method is more accurate,and is capable of performing fault prognosis on the complicated electronic equipment effectively." @default.
- W2367778106 created "2016-06-24" @default.
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- W2367778106 date "2012-01-01" @default.
- W2367778106 modified "2023-09-24" @default.
- W2367778106 title "Fault Prediction for Electronic Equipment Based on Hybrid Support Vector Regression" @default.
- W2367778106 hasPublicationYear "2012" @default.
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