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Investigation of Transfer Learning for Tunnel Support Design
Amichai Mitelman
,
Alon Urlainis
Department of Civil Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
9
Scopus citations
Overview
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Keyphrases
Transfer Learning
100%
Tunnel Support Design
100%
Knowledge Transfer
33%
Tunnel Support
33%
Support Analysis
33%
Machine Learning
16%
Further Development
16%
Machine Learning System
16%
Machine Learning Techniques
16%
Size Limit
16%
Artificial Neural Network
16%
Small Dataset
16%
New Formations
16%
Technical Process
16%
Digital Datasets
16%
Geotechnical Analysis
16%
Geotechnical Applications
16%
Dataset Size
16%
Engineering
Transfer Learning
100%
Tunnel
100%
Learning System
33%
Limitations
16%
Technical Challenge
16%
Machine Learning Technique
16%
Geotechnical Application
16%
Artificial Neural Network
16%
Computer Science
Transfer Learning
100%
Support Analysis
33%
Machine Learning
33%
Learning System
33%
Machine Learning Technique
16%
Large Data Set
16%
Technical Challenge
16%
Size Limitation
16%
Technical Process
16%
Artificial Neural Network
16%
Chemical Engineering
Learning System
100%
Neural Network
33%
Earth and Planetary Sciences
Machine Learning
100%
Artificial Neural Network
33%
Economics, Econometrics and Finance
Machine Learning
100%