关键词: 长短期记忆网络, Prophet模型, 时序预测, 组合预测

Abstract: At present, the single prediction model has low prediction accuracy for complex nonlinear time series and can not capture the composite characteristics of time series well. Therefore, this paper proposes a time series prediction model based on back propagation neural network combination of Long Short-Term Memory-Prophet (LSTM-Prophet). The prediction values obtained from the long short-term memory network and Prophet prediction model are combined by BP neural network to obtain the final prediction value. Then, a comparative experiment is designed and implemented between the proposed model and three individual models. The accuracy and validity of the proposed model are verified by data sets from three different fields. The experimental results show that the proposed prediction model has high prediction accuracy, good universality, and application prospect.

Key words: long short-term memory, Prophet model, time series prediction, combination prediction