Decomposition-Aware Framework for Probabilistic and Flexible Time Series Forecasting in Aerospace Electronic Systems

Yuanhong Mao, Xin Hu (), Yulang Xu, Yilin Zhang, Yunan Li, Zixiang Lu and Qiguang Miao
Additional contact information
Yuanhong Mao: Xi’an Microelectronics Technology Institute, Xi’an 710065, China
Xin Hu: School of Computer Science and Technology, Xidian University, Xi’an 710071, China
Yulang Xu: School of Computer Science and Technology, Xidian University, Xi’an 710071, China
Yilin Zhang: School of Computer Science and Technology, Xidian University, Xi’an 710071, China
Yunan Li: School of Computer Science and Technology, Xidian University, Xi’an 710071, China
Zixiang Lu: School of Computer Science and Technology, Xidian University, Xi’an 710071, China
Qiguang Miao: School of Computer Science and Technology, Xidian University, Xi’an 710071, China

Mathematics, 2025, vol. 13, issue 2, 1-23

Abstract: Degradation prediction for aerospace electronic systems plays a crucial role in maintenance work. This paper proposes a concise and efficient framework for multivariate time series forecasting that is capable of handling diverse sequence representations through a Channel-Independent (CI) strategy. This framework integrates a decomposition-aware layer to effectively separate and fuse global trends and local variations and a temporal attention module to capture temporal dependencies dynamically. This design enables the model to process multiple distinct sequences independently while maintaining the flexibility to learn shared patterns across channels. Additionally, the framework incorporates probabilistic distribution forecasting using likelihood functions, addressing the dynamic variations and uncertainty in time series data. The experimental results on multiple real-world datasets validate the framework’s effectiveness, demonstrating its robustness and adaptability in handling diverse sequences across various application scenarios.

Keywords: multivariate time series forecasting; decomposition-aware layer; channel-independent strategy; probabilistic distribution forecasting (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/2/262/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/2/262/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:2:p:262-:d:1566910

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().