Integration Advanced Neural Networks Technologies: a new Opportunity for economic Time Series Forecasting

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F24%3A10257852" target="_blank" >RIV/61989100:27510/24:10257852 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10900841" target="_blank" >https://ieeexplore.ieee.org/document/10900841</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/Informatics62280.2024.10900841" target="_blank" >10.1109/Informatics62280.2024.10900841</a>

Result language
angličtina
Original language name
Integration Advanced Neural Networks Technologies: a new Opportunity for economic Time Series Forecasting
Original language description
This paper presents the results of integrating transformer outputs into advanced adaptive architectures of convolutional neural networks (CNN) and describes the advantages of this approach compared to baseline models. The novelty of this work lies in the approach to creating models capable of leveraging the strengths of both CNNs and transformers, dynamically adjusting their architecture based on cross-validation results. The strengths of CNNs in handling local patterns through causal convolutions and activation layers are complemented by the transformers' capabilities in processing long-term dependencies, which is crucial for forecasting financial time series that often exhibit noise and unpredictable behavior. Combining these technologies results in robust hybrid forecasting architectures that not only improve validation metrics, indicating higher accuracy in predictions but also reduce model execution time, making them highly practical for forecasting highly dynamic financial series. Additionally, the adaptive approach leads to more stable performance across multiple neural network models with identical parameters, although absolute resolution of this task requires further research.
Czech name
—
Czech description
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Project
<a href="/en/project/TQ12000017" target="_blank" >TQ12000017: RESEARCH CENTER FOR A RESILIENT, SMART, INNOVATIVE AND SUSTAINABLE SOCIETY</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
INFORMATICS 2024 : 2024 IEEE 17th International Scientific Conference on Informatics : November 13-15, 2024, Poprad, Slovakia : proceedings
ISBN
979-8-3503-8769-8
ISSN
—
e-ISSN
—
Number of pages
5
Pages from-to
168-172
Publisher name
IEEE
Place of publication
Piscataway
Event location
Poprad
Event date
Nov 13, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001483035700029

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