Machine learning approach for prediction of TBM performance and risk of jamming in Himalayan geology using a cross-project tunnelling database
- DOI
- 10.1038/s41598-025-34273-z
- Published
- 2026-01-08
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-34273-z,
title = {Machine learning approach for prediction of TBM performance and risk of jamming in Himalayan geology using a cross-project tunnelling database},
author = {Tek Bahadur Katuwal and Krishna Kanta Panthi and Chhatra Bahadur Basnet},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-34273-z},
url = {https://doi.org/10.1038/s41598-025-34273-z}
}RIS
TY - JOUR TI - Machine learning approach for prediction of TBM performance and risk of jamming in Himalayan geology using a cross-project tunnelling database AU - Tek Bahadur Katuwal AU - Krishna Kanta Panthi AU - Chhatra Bahadur Basnet PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-025-34273-z UR - https://doi.org/10.1038/s41598-025-34273-z ER -
APA
Katuwal, T. B., Panthi, K. K., & Basnet, C. B. (2026). Machine learning approach for prediction of TBM performance and risk of jamming in Himalayan geology using a cross-project tunnelling database. Scientific Reports. https://doi.org/10.1038/s41598-025-34273-z
Source records
- crossref · retrieved 2026-09-26T08:20:02.188Z