Rock mass quality classification based on deep learning: A feasibility study for stacked autoencoders
Objective and accurate evaluation of rock mass quality classification is the prerequisite for reliable stability assessment. To develop a tool that can deliver quick and accurate evaluation of rock mass quality, a deep learning approach is developed, which uses stacked autoencoders (SAEs) with sever...
I tiakina i:
| Ngā kaituhi matua: | , , , , , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Elsevier
2023-07-01
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| Rangatū: | Journal of Rock Mechanics and Geotechnical Engineering |
| Ngā marau: | |
| Urunga tuihono: | http://www.sciencedirect.com/science/article/pii/S1674775522001834 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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