Artificial Neural Networks for Predicting Asphalt Fatigue Life: Investigating Material and Loading Parameters with a Comprehensive Dataset and Addressing Model Intricacies

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F25%3A00384945" target="_blank" >RIV/68407700:21110/25:00384945 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-94600-4_5" target="_blank" >https://doi.org/10.1007/978-3-031-94600-4_5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-94600-4_5" target="_blank" >10.1007/978-3-031-94600-4_5</a>

Result language
angličtina
Original language name
Artificial Neural Networks for Predicting Asphalt Fatigue Life: Investigating Material and Loading Parameters with a Comprehensive Dataset and Addressing Model Intricacies
Original language description
This study employs artificial neural networks (ANNs) to pre-dict the fatigue life of asphalt concrete (AC), crucial for road main-tenance and longevity. Leveraging a dataset from extensive laboratory tests, we optimized ANN models to address the variability in AC fatigue data. Our approach involved fine-tuning hyperparameters and adapt-ing network architectures to best utilize a dataset of 152 samples. The models were trained with both linear and logarithmic loss functions. Results showed that modified bituminous binders significantly improve fatigue life predictions, with comprehensive input parameters being vital for accurate modeling. Although models achieved moderate overall R^2R2 scores of about 0.4, they highlighted the significant impact of binder type and content on prediction outcomes. The research demonstrates the potential of machine learning to enhance pavement engineering by pro-viding deeper insights into AC fatigue life. Optimized models and codes are available in an open repository, encouraging further exploration and application.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Futuristic Computational Systems and Advanced Engineering for the Society, Proceedings of the 6th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2024, Volume 2
ISBN
9783031946004
ISSN
2731-5010
e-ISSN
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Number of pages
16
Pages from-to
62-77
Publisher name
Springer Nature Switzerland AG
Place of publication
Basel
Event location
Warsaw
Event date
Sep 26, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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