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A predictive model of water-quality, which based on wavelet transform and support vector machine, is proposed. This model uses wavelet transform to get water time sequence variations in different scale, and optimizes three parameters of Regression Support Vector Machine with improved Particle Swarm Optimization algorithm, to improve the accuracy of prediction model. This model is used to take one-step...
To improve the predication accuracy for server load, a novel predication method was proposed based on the integration of wavelet analysis and support vector regression. The server load time series, which is nonlinear and non-stationary, was decomposed and then, reconstructed into several branches by the wavelet method. Of these branches, the lowest scale high frequency signal was forecasted by moving...
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