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This study presents a busy telephone traffic prediction model that combines wavelet transformation and least squares support vector machine. Firstly, decompose preprocessed telephone traffic data with Mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use LS_SVM model to predict each reconfigure one. Then the traffic can be achieved. The results of experiments have testified higher prediction accuracy and stability of this combined traffic prediction model.

Telephone Traffic Prediction Based on Modified Forecasting Model