Enhancing low-cost PM2.5 air quality monitoring sensors through sensor calibration using regression and echo-state network models
- DOI
- 10.1007/s10661-026-15623-4
- Published
- 2026-06-30
- Container
- Environmental Monitoring and Assessment
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s10661-026-15623-4,
title = {Enhancing low-cost PM2.5 air quality monitoring sensors through sensor calibration using regression and echo-state network models},
author = {Mahesh Senarathna and Gimhan Attanayake and Michael H. Bergin and Prakash V. Bhave and Meththika Vithanage and Nalin Harischandra and Gayan Bowatte},
year = {2026},
journal = {Environmental Monitoring and Assessment},
doi = {10.1007/s10661-026-15623-4},
url = {https://doi.org/10.1007/s10661-026-15623-4}
}RIS
TY - JOUR TI - Enhancing low-cost PM2.5 air quality monitoring sensors through sensor calibration using regression and echo-state network models AU - Mahesh Senarathna AU - Gimhan Attanayake AU - Michael H. Bergin AU - Prakash V. Bhave AU - Meththika Vithanage AU - Nalin Harischandra AU - Gayan Bowatte PY - 2026 JO - Environmental Monitoring and Assessment DO - 10.1007/s10661-026-15623-4 UR - https://doi.org/10.1007/s10661-026-15623-4 ER -
APA
Senarathna, M., Attanayake, G., Bergin, M. H., Bhave, P. V., Vithanage, M., Harischandra, N., & Bowatte, G. (2026). Enhancing low-cost PM2.5 air quality monitoring sensors through sensor calibration using regression and echo-state network models. Environmental Monitoring and Assessment. https://doi.org/10.1007/s10661-026-15623-4
Source records
- crossref · retrieved 2026-09-26T04:20:18.188Z