CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 13513 > Article
Open Access Paper
15 January 2025 Revisiting the efficacy of signal decomposition in AI-based time series prediction
Dan Zhang, Kexin Jiang, Chuhan Wu, Yan Peng, Zhaolong Han, Yaoran Chen
Author Affiliations +
Proceedings Volume 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024); 135130M (2025) https://doi.org/10.1117/12.3045386
Event: The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 2024, Wuhan, China
Abstract
Time series prediction is a fundamental problem in scientific exploration and artificial intelligence (AI) technologies have substantially bolstered its efficiency and accuracy. A well-established paradigm in AI-driven time series prediction is injecting physical knowledge into neural networks through signal decomposition methods, and sustaining progress in numerous scenarios has been reported. However, we uncover non-negligible evidence that challenges the effectiveness of signal decomposition in AI-based time series prediction. We confirm that improper dataset processing with subtle future label leakage is unfortunately widely adopted, possibly yielding abnormally superior but misleading results. By processing data in a strictly causal way without any future information, the effectiveness of additional decomposed signals diminishes. Our work probably identifies an ingrained and universal error in time series modeling, and the de facto progress in relevant areas is expected to be revisited and calibrated to prevent future scientific detours and minimize practical losses.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Dan Zhang, Kexin Jiang, Chuhan Wu, Yan Peng, Zhaolong Han, and Yaoran Chen "Revisiting the efficacy of signal decomposition in AI-based time series prediction", Proc. SPIE 13513, The International Conference Optoelectronic Information and Optical Engineering (OIOE2024), 135130M (15 January 2025); https://doi.org/10.1117/12.3045386
PROCEEDINGS
 10 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling
Education and training
Data processing
Machine learning
Transformers
Signal processing
Artificial intelligence
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top