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Geo-Sustainnovation for Resilient Society Select Proceedings of CREST 2023

Title
Geo-Sustainnovation for Resilient Society [electronic resource] : Select Proceedings of CREST 2023 / edited by Hemanta Hazarika, Stuart Kenneth Haigh, Babloo Chaudhary, Masanori Murai, Suman Manandhar.
ISBN
9789819992195
Edition
1st ed. 2024.
Publication
Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Physical Description
1 online resource (XXV, 403 p.) 250 illus., 224 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book presents select proceedings of the 2nd International Conference on Construction Resources for Environmentally Sustainable Technologies (CREST 2023), and focuses on sustainability, promotion of new ideas and innovations in design, construction and maintenance of geotechnical structures with the aim of contributing towards climate change adaptation and disaster resiliency to meet the UN Sustainable Development Goals (SDGs). It presents latest research, information, technological advancement, practical challenges encountered, and solutions adopted in the field of geotechnical engineering for sustainable infrastructure towards climate change adaptation. This volume will be of interest to those in academia and industry alike.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
April 10, 2024
Series
Lecture Notes in Civil Engineering, 446
Lecture Notes in Civil Engineering, 446
Contents
PART I: Information Based (AI, IoT, VR etc.) Measures for Natural Disaster Mitigation
Chapter 1. A Stratigraphic Classification Estimation Method by the D-Layer Neural Networks
Chapter 2. An Approach for Evacuation Vulnerability Assessment with Consideration of Predicted Evacuation Time
Chapter 3. Development and Applicability Assessment of a Tunnel Face Monitoring System Against Tunnel Face Collapse
Chapter 4. Development of Real-time Measuring System of Tip Position with Deep Mixing Methods
Chapter 5. Evaluation of Landslide Triggering Mechanism during Rainfall in Slopes Containing Vertical Cracks
Chapter 6. Landslide Risk Prediction and Regional Dependence Evaluation Based on Disaster History Using Machine Learning and Deep Learning
Chapter 7. Machine Learning for Estimation of Surface Ground Structure by H/V Spectral Ratio
Chapter 8. Regular Deformation-Based Landslide Potential Detection with DInSAR - A Case Study of Taipei City
Chapter 9. Utilization of AI-BasedDiagnostic Imaging for Advanced and Efficient Tunnel Maintenance. etc.
Citation

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