PUBLICACIÓN
Machine learning methods for low-cost pollen monitoring – Model optimisation and interpretability
ACCEDER A LA PUBLICACIÓN:
Mills S.A., Maya-Manzano J.M., Tummon F., MacKenzie A.R., Pope F.D.
2023 Science of The Total Environment
Environmental Chemistry (Q1), Environmental Engineering (Q1), Pollution (Q1), Waste Management and Disposal (Q1)
JCR: 8.2
SJR: 1.998
CITAS
8
DOI
10.1016/j.scitotenv.2023.165853
EID
2-s2.0-85168418392
ISSN
0048-9697
EISSN
1879-1026
BIBTEX
@article{Mills_2023, doi = {10.1016/j.scitotenv.2023.165853}, url = {https://doi.org/10.1016%2Fj.scitotenv.2023.165853}, year = 2023, month = {dec}, publisher = {Elsevier {BV}}, volume = {903}, pages = {165853}, author = {Sophie A. Mills and Jos{\'{e}} M. Maya-Manzano and Fiona Tummon and A. Rob MacKenzie and Francis D. Pope}, title = {Machine learning methods for low-cost pollen monitoring {\textendash} Model optimisation and interpretability}, journal = {Science of The Total Environment}}
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