Analysis and research of several network traffic prediction models

There are many factors which affect the prediction of network traffic at present. The traditional network traffic prediction model has not met the needs of prediction. Therefore, many scholars have been researching on the area. This paper analyzed network traffic prediction models based on neural network by ant colony optimization algorithm, based on neural network by quantum particle swarm optimization algorithm, and based on neural network by genetic algorithm optimized; studied the forecasting process of these models; compared the forecasting performance of three models. And proposed view for study in the future.

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