Predicting continuous load-settlement trajectories of bored piles: A GA-optimized weighted ensemble framework with explainable AI

Loi Van Giap, Tuong Lai Nguyen, Tuan Anh Pham

Open source

DOI: 10.1371/journal.pone.0360945
Published: 2026-10-21
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0360945,
  title = {Predicting continuous load-settlement trajectories of bored piles: A GA-optimized weighted ensemble framework with explainable AI},
  author = {Loi Van Giap and Tuong Lai Nguyen and Tuan Anh Pham},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0360945},
  url = {https://doi.org/10.1371/journal.pone.0360945}
}

RIS

TY  - JOUR
TI  - Predicting continuous load-settlement trajectories of bored piles: A GA-optimized weighted ensemble framework with explainable AI
AU  - Loi Van Giap
AU  - Tuong Lai Nguyen
AU  - Tuan Anh Pham
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0360945
UR  - https://doi.org/10.1371/journal.pone.0360945
ER  -

APA

Giap, L. V., Nguyen, T. L., & Pham, T. A. (2026). Predicting continuous load-settlement trajectories of bored piles: A GA-optimized weighted ensemble framework with explainable AI. PLOS One. https://doi.org/10.1371/journal.pone.0360945

Source records

crossref · retrieved 2026-11-08T14:45:28.163Z