A deep learning approach to predict Hamburg rutting curve
| Autor: | Punyaslok Rath, William G. Buttlar, Amir H. Alavi, Hamed Majidifard, Behnam Jahangiri |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
050210 logistics & transportation
Artificial neural network Rut Test procedures business.industry Computer science Deep learning 05 social sciences 0211 other engineering and technologies 02 engineering and technology Convolutional neural network Test (assessment) Asphalt concrete 021105 building & construction 0502 economics and business Artificial intelligence business Simulation Civil and Structural Engineering |
| Zdroj: | Road Materials and Pavement Design. 22:2159-2180 |
| ISSN: | 2164-7402 1468-0629 |
| DOI: | 10.1080/14680629.2021.1886160 |
| Popis: | The Hamburg wheel tracking test (HWTT) is a widely used testing procedure designed to accelerate and simulate the rutting phenomena in the laboratory. Rut depth, as one of the outputs of the HWTT, ... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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