Explainable spatiotemporal Graph Neural Networks: Multi-City PM2.5 forecasting in Bangladesh with geographic graph topology validation.

Nobin PR

DOI: 10.1371/journal.pone.0351928
Published: 2026
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0351928,
  title = {Explainable spatiotemporal Graph Neural Networks: Multi-City PM2.5 forecasting in Bangladesh with geographic graph topology validation.},
  author = {Nobin PR},
  year = {2026},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0351928},
  url = {https://doi.org/10.1371/journal.pone.0351928}
}

RIS

TY  - JOUR
TI  - Explainable spatiotemporal Graph Neural Networks: Multi-City PM2.5 forecasting in Bangladesh with geographic graph topology validation.
AU  - Nobin PR
PY  - 2026
JO  - PloS one
DO  - 10.1371/journal.pone.0351928
UR  - https://doi.org/10.1371/journal.pone.0351928
ER  -

APA

PR, N. (2026). Explainable spatiotemporal Graph Neural Networks: Multi-City PM2.5 forecasting in Bangladesh with geographic graph topology validation.. PloS one. https://doi.org/10.1371/journal.pone.0351928

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pubmed · retrieved 2026-11-10T20:15:59.827Z