Exo-lstm: Traffic flow prediction based on multifractal wavelet theory

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. © 2021, Beijing University of Posts and Telecommunications. All rights reserved.