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In the analysis of predicting share price based on least squares support vector machine (LS-SVM), the instability of the time series could lead to decrease of prediction accuracy. On the other hand, three SVM parameters, c, epsiv and sigma, must be carefully predetermined in establishing an efficient LS-SVM model. In order to solve the problems mentioned above, in this paper, the hybrid of wavelet...
Analog fault diagnosis has been an active area of research since the mid-1970s, now many diagnosis methods use neural networks. But it needs lots of fault samples and it is also not easy to train the neural network. We have presented a analog-circuit fault diagnosis method based on LS-SVM. To reduce the fault feature vectors to train LS-SVM, we use the energy of high frequency of wavelet transform...
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