scholarly journals Prediction of chaotic time series using hybrid neural network and attention mechanism

2021 ◽  
Vol 70 (1) ◽  
pp. 010501-010501
Author(s):  
Huang Wei-Jian ◽  
◽  
Li Yong-Tao ◽  
Huang Yuan
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Chaotic Time Series ◽  
Attention Mechanism ◽  
Hybrid Neural Network

Prediction of Chaotic Time Series Based on the Recurrent Predictor Neural Network

2004 ◽  
Vol 52 (12) ◽  
pp. 3409-3416 ◽  
Author(s):  
M. Han ◽  
J. Xi ◽  
S. Xu ◽  
F.-L. Yin
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Chaotic Time Series

scholarly journals A Hybrid Model Based on a Two-Layer Decomposition Approach and an Optimized Neural Network for Chaotic Time Series Prediction

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 610 ◽  
Author(s):  
Xinghan Xu ◽  
Weijie Ren
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hybrid Model ◽  
Back Propagation ◽  
Research Field ◽  
Chaotic Time Series ◽  
Good Prospect ◽  
Decomposition Approach ◽  
Model Based ◽  
Mode Decomposition

The prediction of chaotic time series has been a popular research field in recent years. Due to the strong non-stationary and high complexity of the chaotic time series, it is difficult to directly analyze and predict depending on a single model, so the hybrid prediction model has become a promising and favorable alternative. In this paper, we put forward a novel hybrid model based on a two-layer decomposition approach and an optimized back propagation neural network (BPNN). The two-layer decomposition approach is proposed to obtain comprehensive information of the chaotic time series, which is composed of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and variational mode decomposition (VMD). The VMD algorithm is used for further decomposition of the high frequency subsequences obtained by CEEMDAN, after which the prediction performance is significantly improved. We then use the BPNN optimized by a firefly algorithm (FA) for prediction. The experimental results indicate that the two-layer decomposition approach is superior to other competing approaches in terms of four evaluation indexes in one-step and multi-step ahead predictions. The proposed hybrid model has a good prospect in the prediction of chaotic time series.

Sign in / Sign up

Export Citation Format

Share Document