| A hybrid model for spatiotemporal forecasting of PM2. 5 based on graph convolutional neural network and long short-term memory Y Qi, Q Li, H Karimian, D Liu Science of the Total Environment 664, 1-10, 2019 | 510 | 2019 |
| A spatiotemporal prediction framework for air pollution based on deep RNN J Fan, Q Li, J Hou, X Feng, H Karimian, S Lin ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2017 | 213 | 2017 |
| Evaluation of Different Machine Learning Approaches to Forecasting PM2.5 Mass Concentrations H Karimian, Q Li, C Wu, Y Qi, Y Mo, G Chen, X Zhang, S Sachdeva Aerosol and Air Quality Research 19 (6), 1400-1410, 2019 | 156 | 2019 |
| Landscape ecological risk assessment and driving factor analysis in Dongjiang river watershed H Karimian, W Zou, Y Chen, J Xia, Z Wang Chemosphere 307, 2022 | 110 | 2022 |
| Spatio-temporal variation of ozone pollution risk and its influencing factors in China based on Geodetector and Geospatial models Y Chen, H Li, H Karimian*, M Li, Q Fan, Z Xu Chemosphere, 134843, 2022 | 69 | 2022 |
| Spatio‑temporal distribution characteristics and influencing factors of COVID‑19 in China Y Chen*, Q Li, H Karimian*, X Chen, X Li Scientific Reports 11, 2021 | 47 | 2021 |
| An improved method for monitoring fine particulate matter mass concentrations via satellite remote sensing H Karimian, Q Li, C Li, L Jin, J Fan, Y Li Aerosol and Air Quality Research 16 (4), 1081-1092, 2016 | 46* | 2016 |
| A novel framework for daily forecasting of ozone mass concentrations based on cycle reservoir with regular jumps neural networks Y Mo, Q Li, H Karimian, S Fang, B Tang, G Chen, S Sachdeva Atmospheric environment 220, 117072, 2020 | 43 | 2020 |
| Evaluation of different machine learning approaches and aerosol optical depth in PM2. 5 prediction H Karimian, Y Li, Y Chen, Z Wang Environmental Research 216, 114465, 2023 | 42 | 2023 |
| DESA: a novel hybrid decomposing‑ensemble and spatiotemporal attention model for PM2.5 forecasting S Fang, Q Li, H Karimian*, H Liu, Y Mo Environmental Science and Pollution Research, 2022 | 31 | 2022 |
| Daily spatiotemporal prediction of surface ozone at the national level in China: an improvement of CAMS ozone product Y Mo, Q Li, H Karimian, S Zhang, X Kong, S Fang, B Tang Atmospheric Pollution Research 12 (1), 391-402, 2021 | 29 | 2021 |
| A novel framework for prediction of dam deformation based on extreme learning machine and Lévy flight bat algorithm Y Chen, X Zhang, H Karimian, G Xiao, J Huang Journal of Hydroinformatics 23 (5), 935-949, 2021 | 25 | 2021 |
| Spatio-temporal variation of wind influence on distribution of fine particulate matter and its precursor gases H Karimian, Q Li, C Li, G Chen, Y Mo, C Wu, J Fan Atmospheric Pollution Research 10 (1), 53-64, 2019 | 25 | 2019 |
| PM2. 5 concentration prediction using convolutional neural networks C Wu, Q Li, J Hou, H Karimian, G Chen Sci. Surv. Mapp 43, 68-75, 2018 | 23 | 2018 |
| Assessing urban sustainable development in Isfahan H Karimian, Q Li, HF Chen Applied Mechanics and Materials 253, 244-248, 2013 | 22 | 2013 |
| Daily estimation of fine particulate matter mass concentration through satellite based aerosol optical depth H Karimian, Q Li, CC Li, J Fan, L Jin, C Gong, Y Mo, J Hou, A Ahmad ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2017 | 21 | 2017 |
| Henan Ecological Security Evaluation Using Improved 3D Ecological Footprint Model Based on Emergy and Net Primary Productivity C Gong, L Qi, P Fei, H Karimian, T , Boyuan sustainability 11, 2019 | 20 | 2019 |
| The relationship between air quality and MODIS aerosol optical depth in major cities of the Yangtze River Delta Y Chen, D Li, H Karimian, S Wang, S Fang Chemosphere 308, 136301, 2022 | 18 | 2022 |
| Spatiotemporal analysis of air quality and its relationship with meteorological factors in the Yangtze River Delta. Y Li, Y Chen, H Karimian, T Tian Journal of Elementology 25, 1059-1075, 2020 | 18 | 2020 |
| A novel framework to predict chlorophyll-a concentrations in water bodies through multi-source big data and machine learning algorithms H Karimian, J Huang, Y Chen, Z Wang, J Huang Environmental Science and Pollution Research 30 (32), 79402-79422, 2023 | 14 | 2023 |