Advanced Methods for Time Series Forecasting
Language: English
Published by MDPI AG, 2026
- Hardcover
- New

Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
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Seller Inventory # L2-9783725869404
- Title
- Advanced Methods for Time Series Forecasting
- Publisher
- MDPI AG
- Publication year
- 2026
- Condition
- New
- Binding
- HRD
- Language
- English
- ISBN 10
- 3725869405
- ISBN 13
- 9783725869404
- Item weight
- 803 grams
This Special Issue, "Advanced Methods for Time Series Forecasting", focuses on recent methodological and applied advances that address the complex modern time series data. As forecasting has been increasingly used in decision-making in various research-related fields such as, but not limited to energy systems, finance, transportation, smart infrastructure, environmental modeling, and management science, the need for models that can capture nonlinear dynamics, long-term dependencies, multiscale patterns, and uncertainty is real and actual.
The Special Issue provides an innovative approach to the issues associated with the time series forecasting, spanning artificial intelligence, deep learning, hybrid statistical-machine learning models, attention mechanisms, transformer-based architectures, state-space formulations, and signal decomposition techniques. Contributions featured in the Special Issue include theoretical developments, as well as empirical studies, comparative evaluations, and domain-driven applications which have the role to demonstrate the extent to which the advanced forecasting methods outperform traditional techniques in challenging real-world settings. By bridging together various perspectives and real-life application contexts, this Special Issue aims to provide an overview of current trends, as well as to offer practical solutions, and future research directions in advanced time series forecasting.
"Synopsis" may belong to another edition of this title.
PBShop.store UK
Fairford, GLOS, United Kingdom
AbeBooks seller since June 11, 1999
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