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Exo-LSTM: traffic flow prediction based on multifractal wavelet theory

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摘要 In order to predict traffic flow more accurately and improve network performance, based on the multifractal wavelet theory, a new traffic prediction model named exo-LSTM is proposed. Exo represents exogenous sequence used to provide a detailed sequence for the model, LSTM represents long short-term memory used to predict unstable traffic flow. Applying multifractal traffic flow to the exo-LSTM model and other existing models, the experiment result proves that exo-LSTM prediction model achieves better prediction accuracy.
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2021年第5期102-110,共9页 中国邮电高校学报(英文版)
基金 supported by the National Key Research and Development Program of China (2018YFB180060) the Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory Research Project (SKX192010028)。

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