Advanced Deep Learning Architectures for Time Series Forecasting: From Traditional Models to Complex Neural Frameworks

Authors

  • Premanand Tiwari

Keywords:

Deep Learning Architectures, Time Series Forecasting, Temporal Convolutional Networks, Attention Mechanisms, Hybrid Modeling Approaches

Abstract

Advanced deep learning architectures have fundamentally transformed time series forecasting acrossdomains by addressing the limitations of traditional statistical methods. This article traces the evolution from classical models

References

Omer Berat Sezer et al., "Financial time series forecasting with deep learning: A systematic literature

review: 2005–2019," ScienceDirect, 2020.

https://www.sciencedirect.com/science/article/abs/pii/S1568494620301216

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Published

2025-11-12

How to Cite

Premanand Tiwari. (2025). Advanced Deep Learning Architectures for Time Series Forecasting: From Traditional Models to Complex Neural Frameworks . Journal of Computational Analysis and Applications (JoCAAA), 34(11), 137–154. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4107

Issue

Vol. 34 No. 11 (2025): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.