AI-enhanced safety evaluation for tunnelling in rock : principles, methods and algorithms /
Artificial intelligence (AI) techniques for rock tunnel construction offer innovative solutions for assessing rock mass quality and ensuring excavation safety in challenging geological conditions. Both cutting-edge contact methods and noncontact methods such as digital photography can provide contin...
| Main Authors: | , , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
CRC Press, Taylor and Francis Group,
2026.
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| Edition: | First edition. |
| Series: | Challenges in geotechnical and rock engineering.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Artificial intelligence (AI) techniques for rock tunnel construction offer innovative solutions for assessing rock mass quality and ensuring excavation safety in challenging geological conditions. Both cutting-edge contact methods and noncontact methods such as digital photography can provide continuous geological data during excavation. Then, advanced deep learning algorithms for precise characterization of rock face features, along with pioneering multisource 3D data fusion modelling, can enable refined rock mass classification and sophisticated safety evaluation techniques tailored to complex geological environments. By integrating machine vision and intelligent algorithms with rigorous statistical analysis and machine learning models, this book provides practical and refined solutions for the construction industry. It offers improved safety, efficiency, and reliability for tunnel projects and serves as a valuable reference for graduate students and academics. |
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| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 9781040453636 1040453635 9781040453667 104045366X 9781003595557 1003595553 |