Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system
- DOI
- 10.3389/frobt.2026.1846010
- Published
- 2026-05-26
- Container
- Frontiers in Robotics and AI
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/frobt.2026.1846010,
title = {Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system},
author = {Mingyu Zhao and Shujia Zhang and Ke Li and Yanru Zhang and Xiyi Wang and Tianyue Chen and Yawen Ren and Yuxi Lu and Jiahe Wang},
year = {2026},
journal = {Frontiers in Robotics and AI},
doi = {10.3389/frobt.2026.1846010},
url = {https://doi.org/10.3389/frobt.2026.1846010}
}RIS
TY - JOUR TI - Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system AU - Mingyu Zhao AU - Shujia Zhang AU - Ke Li AU - Yanru Zhang AU - Xiyi Wang AU - Tianyue Chen AU - Yawen Ren AU - Yuxi Lu AU - Jiahe Wang PY - 2026 JO - Frontiers in Robotics and AI DO - 10.3389/frobt.2026.1846010 UR - https://doi.org/10.3389/frobt.2026.1846010 ER -
APA
Zhao, M., Zhang, S., Li, K., Zhang, Y., Wang, X., Chen, T., Ren, Y., Lu, Y., & Wang, J. (2026). Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system. Frontiers in Robotics and AI. https://doi.org/10.3389/frobt.2026.1846010
Source records
- crossref · retrieved 2026-11-04T09:42:33.381Z