A dual‐stage attention‐based Conv‐LSTM network for spatio‐temporal correlation and multivariate time series prediction

2021 ◽  
Author(s):  
Yuteng Xiao ◽  
Hongsheng Yin ◽  
Yudong Zhang ◽  
Honggang Qi ◽  
Yundong Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Prediction ◽  
Multivariate Time Series ◽  
Temporal Correlation ◽  
Dual Stage ◽  
Spatio Temporal ◽  
Lstm Network

scholarly journals Compound Autoregressive Network for Prediction of Multivariate Time Series

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yuting Bai ◽  
Xuebo Jin ◽  
Xiaoyi Wang ◽  
Tingli Su ◽  
Jianlei Kong ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Prediction ◽  
Multivariate Time Series ◽  
Prediction Algorithm ◽  
Short Term ◽  
Advanced Control ◽  
Multiple Variables ◽  
Nonlinear Autoregressive Model ◽  
Interactive Relation ◽  
Nonlinear Autoregressive

The prediction information has effects on the emergency prevention and advanced control in various complex systems. There are obvious nonlinear, nonstationary, and complicated characteristics in the time series. Moreover, multiple variables in the time-series impact on each other to make the prediction more difficult. Then, a solution of time-series prediction for the multivariate was explored in this paper. Firstly, a compound neural network framework was designed with the primary and auxiliary networks. The framework attempted to extract the change features of the time series as well as the interactive relation of multiple related variables. Secondly, the structures of the primary and auxiliary networks were studied based on the nonlinear autoregressive model. The learning method was also introduced to obtain the available models. Thirdly, the prediction algorithm was concluded for the time series with multiple variables. Finally, the experiments on environment-monitoring data were conducted to verify the methods. The results prove that the proposed method can obtain the accurate prediction value in the short term.

Multiple convolutional neural networks for multivariate time series prediction

2019 ◽  
Vol 360 ◽  
pp. 107-119 ◽  
Author(s):  
Kang Wang ◽  
Kenli Li ◽  
Liqian Zhou ◽  
Yikun Hu ◽  
Zhongyao Cheng ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Convolutional Neural Networks ◽  
Time Series Prediction ◽  
Multivariate Time Series
Sign in / Sign up

Export Citation Format

Share Document