A Novel Hybrid Approach For Efficiently Forecasting Air Quality Data
- DOI
- 10.1109/lsens.2024.3519719
- Published
- 2025-01
- Container
- IEEE Sensors Letters
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/lsens.2024.3519719,
title = {A Novel Hybrid Approach For Efficiently Forecasting Air Quality Data},
author = {Jintu Borah and Tanujit Chakraborty and Md. Shahrul Md. Nadzir and Mylene G. Cayetano and Francesco Benedetto and Shubhankar Majumdar},
year = {2025},
journal = {IEEE Sensors Letters},
doi = {10.1109/lsens.2024.3519719},
url = {https://doi.org/10.1109/lsens.2024.3519719}
}RIS
TY - JOUR TI - A Novel Hybrid Approach For Efficiently Forecasting Air Quality Data AU - Jintu Borah AU - Tanujit Chakraborty AU - Md. Shahrul Md. Nadzir AU - Mylene G. Cayetano AU - Francesco Benedetto AU - Shubhankar Majumdar PY - 2025 JO - IEEE Sensors Letters DO - 10.1109/lsens.2024.3519719 UR - https://doi.org/10.1109/lsens.2024.3519719 ER -
APA
Borah, J., Chakraborty, T., Nadzir, M. S. M., Cayetano, M. G., Benedetto, F., & Majumdar, S. (2025). A Novel Hybrid Approach For Efficiently Forecasting Air Quality Data. IEEE Sensors Letters. https://doi.org/10.1109/lsens.2024.3519719
Source records
- crossref · retrieved 2026-09-26T23:36:58.243Z