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Asphalt Concrete Mix Design Optimization Using Autoencoder Deep Neural Networks
José Rivera-Pérez
,
Imad L. Al-Qadi
Civil and Environmental Engineering
Grainger College of Engineering
Center for South Asian and Middle Eastern Studies
Research output
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peer-review
Overview
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Dive into the research topics of 'Asphalt Concrete Mix Design Optimization Using Autoencoder Deep Neural Networks'. Together they form a unique fingerprint.
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Engineering
Asphalt Concrete
20%
Autoencoder
100%
Binder Content
60%
Concrete Mix
100%
Data Preprocessing
20%
Deep Neural Network
100%
Design Alternative
20%
Design Optimization
100%
Hidden Layer
40%
Input Data
20%
Mixing Design
60%
Nodes
20%
Pavement
20%
Test Result
40%
Material Science
Asphalt Concrete
100%
Pavement
25%
Keyphrases
Volumetric Content
20%