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- W2375321769 abstract "In order to identify the two-phase flow regime,a novel method of flow regime identification based on support vector machine and wavelet packet multi-scale information entropy was proposed.The collected differential pressure fluctuation signals were decomposed by the three-layer wavelet packets,and the eight signals of different frequency bands were obtained.The wavelet packet multi-scale information entropy of different frequency bands signals were taken as feature vectors of flow regimes.The feature vector were put into support vector machine and trained to realize the flow regime identification.The result showed that the SVM had higher identification accuracy than BP neural network.The results proved that the method is efficient and feasible." @default.
- W2375321769 created "2016-06-24" @default.
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- W2375321769 date "2007-01-01" @default.
- W2375321769 modified "2023-09-23" @default.
- W2375321769 title "A Novel Identification Method of Gas-liquid Two-phase Flow Regimes Based on Support Vector Machine" @default.
- W2375321769 hasPublicationYear "2007" @default.
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