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...
| 出版年: | Journal of Rock Mechanics and Geotechnical Engineering |
|---|---|
| 主要な著者: | , , , , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
Elsevier
2023-07-01
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| 主題: | |
| オンライン･アクセス: | http://www.sciencedirect.com/science/article/pii/S1674775522001834 |