| Exploring the power of machine learning to predict carbon dioxide trapping efficiency in saline aquifers for carbon geological storage project M Safaei-Farouji, HV Thanh, Z Dai, A Mehbodniya, M Rahimi, U Ashraf, ... Journal of Cleaner Production 372, 133778, 2022 | 47 | 2022 |
| Synergetic effect of N/O functional groups and microstructures of activated carbon on supercapacitor performance by machine learning M Rahimi, MH Abbaspour-Fard, A Rohani Journal of Power Sources 521, 230968, 2022 | 46 | 2022 |
| A multi-data-driven procedure towards a comprehensive understanding of the activated carbon electrodes performance (using for supercapacitor) employing ANN technique M Rahimi, MH Abbaspour-Fard, A Rohani Renewable Energy 180, 980-992, 2021 | 36 | 2021 |
| Machine learning approaches to rediscovery and optimization of hydrogen storage on porous bio-derived carbon M Rahimi, MH Abbaspour-Fard, A Rohani Journal of Cleaner Production 329, 129714, 2021 | 33 | 2021 |
| Modeling and classifying the in-operando effects of wear and metal contaminations of lubricating oil on diesel engine: A machine learning approach M Rahimi, MR Pourramezan, A Rohani Expert Systems with Applications 203, 117494, 2022 | 23 | 2022 |
| Modeling and Optimizing N/O-Enriched Bio-Derived Adsorbents for CO2 Capture: Machine Learning and DFT Calculation Approaches M Rahimi, MH Abbaspour-Fard, A Rohani, O Yuksel Orhan, X Li Industrial & Engineering Chemistry Research 61 (30), 10670-10688, 2022 | 19 | 2022 |
| Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and storage H Zhang, HV Thanh, M Rahimi, WJ Al-Mudhafar, S Tangparitkul, T Zhang, ... Science of The Total Environment 877, 162944, 2023 | 16 | 2023 |
| Predicting the wettability rocks/minerals-brine-hydrogen system for hydrogen storage: Re-evaluation approach by multi-machine learning scheme HV Thanh, M Rahimi, Z Dai, H Zhang, T Zhang Fuel 345, 128183, 2023 | 14 | 2023 |
| Towards the modeling and prediction of the yield of oilseed crops: A multi-machine learning approach M Parsaeian, M Rahimi, A Rohani, SS Lawson Agriculture 12 (10), 1739, 2022 | 10 | 2022 |
| Yield prediction and optimization of biomass-based products by multi-machine learning schemes: Neural, regression and function-based techniques M Rahimi, H Mashhadimoslem, HV Thanh, B Ranjbar, MS Khosrowshahi, ... Energy 283, 128546, 2023 | 7 | 2023 |
| A multi-criteria decision-making (MCDM) approach to determine the synthesizing routes of biomass-based carbon electrode material in supercapacitors M Rahimi, HV Thanh, I Ebrahimzade, MH Abbaspour-Fard, A Rohani Journal of Cleaner Production 397, 136606, 2023 | 7 | 2023 |
| Hydrogen storage on porous carbon adsorbents: rediscovery by nature-derived algorithms in random forest machine learning model HV Thanh, S Ebrahimnia Taremsari, B Ranjbar, H Mashhadimoslem, ... Energies 16 (5), 2348, 2023 | 7 | 2023 |
| Toward Modeling the In Vitro Gas Production Process by Using Propolis Extract Oil Treatment: Machine Learning and Kinetic Models AR Vakili, S Ehtesham, M Danesh-Mesgaran, A Rohani, M Rahimi Industrial & Engineering Chemistry Research 62 (37), 14910-14922, 2022 | 4 | 2022 |
| Catalyzing net-zero carbon strategies: Enhancing CO2 flux Prediction from underground coal fires using optimized machine learning models H Zhang, P Wang, M Rahimi, HV Thanh, Y Wang, Z Dai, Q Zheng, Y Cao Journal of Cleaner Production 441, 141043, 2024 | 2 | 2024 |
| Natural Products Derived Porous Carbons for CO2 Capture MS Khosrowshahi, H Mashhadimoslem, H Shayesteh, G Singh, ... Advanced Science 10 (36), 2304289, 2023 | 1 | 2023 |
Abbas RohaniDepartment of Biosystems Engineering, Agriculture Ferdowsi University of MashhadVerified email at um.ac.ir
