Enhancing Multivariate Time Series Forecasting: A Novel Approach with Mallows Model Averaging and Graph Neural Networks

• Published in: Journal of systems science and complexity Vol. 38; no. 4; pp. 1707 - 1729
• Main Authors: Zhang, Haili, Wang, Jiawei, Liu, Zhaobo, Dong, Hailing
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2025; Springer Nature B.V
• Subjects: Complex Systems; Control; Deep learning; Feature extraction; Forecasting; Graph neural networks; Mathematics; Mathematics and Statistics; Mathematics of Computing; Modules; Multivariate analysis; Network reliability; Neural networks; Operations Research/Decision Theory; Parameters; Statistics; Systems Theory; Time series; model averaging; multivariate time series; Graph neural networks

Multivariate time series forecasting holds substantial practical significance, facilitates precise predictions, and informs decision-making. The complexity of nonlinear relationships and the presence of higher-order features in multivariate time series data have sparked a burgeoning interest in leve...