%0 Journal Article %1 samad2023pollution %A Samad, Abdul %A Garuda, S. %A Vogt, Ulrich %A Yang, Bin %D 2023 %I Elsevier %J Atmospheric environment %K mult oa ubs_10004 ubs_10005 ubs_20004 ubs_20007 ubs_30043 ubs_30077 ubs_40070 ubs_40491 unibibliografie wos %P 119987 %R 10.1016/j.atmosenv.2023.119987 %T Air pollution prediction using machine learning techniques : An approach to replace existing monitoring stations with virtual monitoring stations %V 310

@article{samad2023pollution, added-at = {2024-01-16T11:27:55.000+0100}, affiliation = {Samad, A (Corresponding Author), Univ Stuttgart, Dept Flue Gas Cleaning & Air Qual Control, Inst Combust & Power Plant Technol IFK, Pfaffenwaldring 23, D-70569 Stuttgart, Germany. Samad, A.; Vogt, U., Univ Stuttgart, Dept Flue Gas Cleaning & Air Qual Control, Inst Combust & Power Plant Technol IFK, Stuttgart, Germany. Garuda, S.; Yang, B., Univ Stuttgart, Inst Signal Proc & Syst Theory ISS, Stuttgart, Germany. Samad, A., Univ Stuttgart, Dept Flue Gas Cleaning & Air Qual Control, Inst Combust & Power Plant Technol IFK, Pfaffenwaldring 23, D-70569 Stuttgart, Germany.}, author = {Samad, Abdul and Garuda, S. and Vogt, Ulrich and Yang, Bin}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2411a82fa1be1a5b6b18244e94bb780d9/unibiblio}, doi = {10.1016/j.atmosenv.2023.119987}, interhash = {6599f7bca179b58f591194fe4ed14e2f}, intrahash = {411a82fa1be1a5b6b18244e94bb780d9}, issn = {{1352-2310} and {1873-2844}}, journal = {Atmospheric environment}, keywords = {mult oa ubs_10004 ubs_10005 ubs_20004 ubs_20007 ubs_30043 ubs_30077 ubs_40070 ubs_40491 unibibliografie wos}, language = {eng}, pages = 119987, publisher = {Elsevier}, research-areas = {Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences}, timestamp = {2024-01-16T11:27:55.000+0100}, title = {Air pollution prediction using machine learning techniques : An approach to replace existing monitoring stations with virtual monitoring stations}, unique-id = {WOS:001051204000001}, volume = 310, year = 2023 }