Skip to content
DraconiticResearch
Search Sources API
182,469 studies31 sourcesUpdated 51 min ago
Peer-reviewedCC BY-NC-ND 4.0Scientific Reports

Station-specific variability and short-term forecasting of a particulate air-quality index using machine learning in Charleroi, Belgium

Related

  1. Forecasting threshold exceedance of atmospheric variables at a specific location
    Roberta Baggio, Jean-François Muzy
    HALPreprintarXiv licenceFull textAtmospheric science & meteorologyEnvironmental science & pollutionHALarXiv
  2. Hybrid machine learning framework for drought forecasting: integration of LSBoost, RQNN, CNN-RNN, CNN-LSTM and advanced data decomposition
    Hatice Çıtakoğlu, Pınar Spor, Volkan Gündüz +1
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full text1 citedEnvironmental science & pollutionCrossref
  3. Advancing Near-Term Water Quality Forecasting with Explainable Machine Learning and Probabilistic Uncertainty Quantification
    Rohit Shukla, Cayelan C. Carey, Adrienne Breef-Pilz +1
    ACS ES&T waterPeer-reviewedCC BYFull textEnvironmental science & pollutionEurope PMC
  4. Intra- and inter-specific variability in benthic foraminifera modulates surface sediment reworking
    Manon Doutrelant, Vincent M. P. Bouchet, Emmanuelle Geslin +4
    Royal Society Open SciencePeer-reviewedCC BY 4.0Full textGeneral biologyEnvironmental science & pollutionCrossrefHAL
  5. Station-specific thunderstorm forecasting using climate predictors with seasonal decomposition analysis in Bangladesh’s most vulnerable regions
    Mohammad Mahboob Hussain Khan, Amrin Binte Ahmed, Adisha Dulmini +6
    PLOS OnePeer-reviewedCC BY 4.0Full textAtmospheric science & meteorologyGeophysics & seismologyPLOS
BibTeX
@article{bennis2026stationspecific,
  title = {{Station-specific variability and short-term forecasting of a particulate air-quality index using machine learning in Charleroi, Belgium}},
  author = {Mohamed Bennis and Rachida El Morabet and Eric Hallot and Roohul Abad Khan and Mohamed Youssfi},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-73024-6},
  url = {https://www.nature.com/articles/s41598-026-73024-6},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Station-specific variability and short-term forecasting of a particulate air-quality index using machine learning in Charleroi, Belgium
AU  - Mohamed Bennis
AU  - Rachida El Morabet
AU  - Eric Hallot
AU  - Roohul Abad Khan
AU  - Mohamed Youssfi
PY  - 2026
DA  - 2026/10/20
JO  - Scientific Reports
DO  - 10.1038/s41598-026-73024-6
UR  - https://www.nature.com/articles/s41598-026-73024-6
SN  - 2045-2322
ER  -