DeepGate: Global-local Decomposition for Multivariate Time Series Modeling

2022 ◽  
Author(s):  
Jinuk Park ◽  
Chanhee Park ◽  
Jonghwan Choi ◽  
Sanghyun Park
Keyword(s):  
Time Series ◽  
Multivariate Time Series ◽  
Time Series Modeling

Denoising Multivariate Time Series Modeling for Multi-step Time Series Prediction

2021 ◽  
Vol 48 (8) ◽  
pp. 892-904
Author(s):  
Jungsoo Hong ◽  
Jinuk Park ◽  
Jieun Lee ◽  
Kyeonghun Kim ◽  
Seung-Kyun Hong ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Prediction ◽  
Multivariate Time Series ◽  
Time Series Modeling

MULTIVARIATE TIME SERIES MODELING IN A CONNECTIONIST APPROACH

2000 ◽  
Vol 11 (01) ◽  
pp. 159-173
Author(s):  
D. R. KULKARNI ◽  
J. C. PARIKH
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Series Data ◽  
Time Series Modeling ◽  
Multivariate Models ◽  
Short Term ◽  
Several Variables ◽  
Connectionist Approach

Multivariate models in the framework of artificial neural network have been constructed for systems where time series data of several variables is known. The models have been tested using computer generated data for the Lorenz and Henon systems. They are found to be robust and give accurate short term predictions. Analysis of the models is able to throw some light on theoretical questions related to multivariate "embedding" and removal of redundancy in the embedding.

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