Graph correlated attention recurrent neural network for multivariate time series forecasting

X Geng, X He, L Xu, J Yu - Information Sciences, 2022 - Elsevier
Multivariate time series (MTS) forecasting is an urgent problem for numerous valuable
applications. At present, attention-based methods can relieve recurrent neural networks' …

Correlational graph attention-based Long Short-Term Memory network for multivariate time series prediction

S Han, H Dong, X Teng, X Li, X Wang - Applied Soft Computing, 2021 - Elsevier
Multi-variate time series prediction models use the historical information of multiple
exogenous series to predict the future values of the target series. At present, attention-based …

Multi-scale adaptive graph neural network for multivariate time series forecasting

L Chen, D Chen, Z Shang, B Wu… - … on Knowledge and …, 2023 - ieeexplore.ieee.org
Multivariate time series (MTS) forecasting plays an important role in the automation and
optimization of intelligent applications. It is a challenging task, as we need to consider both …

A long-term multivariate time series forecasting network combining series decomposition and convolutional neural networks

X Wang, H Liu, J Du, X Dong, Z Yang - Applied Soft Computing, 2023 - Elsevier
In multivariate time series forecasting tasks, expanding forecast length and improving
forecast efficiency is an urgent need for practical applications. Accurate long-term …

Multi-step forecasting of multivariate time series using multi-attention collaborative network

X He, S Shi, X Geng, J Yu, L Xu - Expert Systems with Applications, 2023 - Elsevier
Multi-step forecasting of multivariate time series plays a critical role in many fields, such as
disaster warning and financial analysis. While attention-based recurrent neural networks …

CATN: Cross attentive tree-aware network for multivariate time series forecasting

H He, Q Zhang, S Bai, K Yi, Z Niu - … of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
Modeling complex hierarchical and grouped feature interaction in the multivariate time
series data is indispensable to comprehend the data dynamics and predicting the future …

Hierarchical attention network for multivariate time series long-term forecasting

H Bi, L Lu, Y Meng - Applied Intelligence, 2023 - Springer
Multivariate time series long-term forecasting has always been the subject of research in
various fields such as economics, finance, and traffic. In recent years, attention-based …

MrCAN: Multi-relations aware convolutional attention network for multivariate time series forecasting

J Zhang, Q Dai - Information Sciences, 2023 - Elsevier
Multivariate time series forecasting (MTSF) has gathered extensive attention in various
research areas. Many researchers leverage deep neural networks to explore spatial …

A hybrid framework for multivariate long-sequence time series forecasting

X Wang, Y Wang, J Peng, Z Zhang, X Tang - Applied Intelligence, 2023 - Springer
Time series forecasting provides insights into the far future by utilizing the available history
observations. Recent studies have demonstrated the superiority of transformer-based …

Graphformer: Adaptive graph correlation transformer for multivariate long sequence time series forecasting

Y Wang, H Long, L Zheng, J Shang - Knowledge-Based Systems, 2024 - Elsevier
Accurate long sequence time series forecasting (LSTF) remains a key challenge due to its
complex time-dependent nature. Multivariate time series forecasting methods inherently …