| Predictive modeling of biomass gasification with machine learning-based regression methods F Elmaz, Ö Yücel, AY Mutlu Energy 191, 116541, 2020 | 181 | 2020 |
| CNN-LSTM architecture for predictive indoor temperature modeling F Elmaz, R Eyckerman, W Casteels, S Latré, P Hellinckx Building and Environment 206, 108327, 2021 | 130 | 2021 |
| Hilbert vibration decomposition-based epileptic seizure prediction with neural network B Büyükçakır, F Elmaz, AY Mutlu Computers in biology and medicine 119, 103665, 2020 | 54 | 2020 |
| Classification of solid fuels with machine learning F Elmaz, B Büyükçakır, Ö Yücel, AY Mutlu Fuel 266, 117066, 2020 | 36 | 2020 |
| Data-driven identification and model predictive control of biomass gasification process for maximum energy production F Elmaz, Ö Yücel Energy 195, 117037, 2020 | 36 | 2020 |
| Evaluating the effect of blending ratio on the co-gasification of high ash coal and biomass in a fluidized bed gasifier using machine learning F Elmaz, Ö Yücel, AY Mutlu Mugla Journal of Science and Technology 5 (1), 1-12, 2019 | 19 | 2019 |
| Autonomous building control using offline reinforcement learning J Schepers, R Eyckerman, F Elmaz, W Casteels, S Latré, P Hellinckx Advances on P2P, Parallel, Grid, Cloud and Internet Computing: Proceedings …, 2022 | 7 | 2022 |
| Stochastic optimization of pid parameters for twin rotor system with multiple nonlinear regression B Büyükçakir, F Elmaz, S Sahin, L Aydin 2018 6th international conference on control engineering & information …, 2018 | 7 | 2018 |
| Makine Öğrenmesi ile Kısa ve Elemental Analiz Kullanarak Katı Yakıtların Üst Isı Değerinin Tahmin Edilmesi F Elmaz, Ö Yücel, AY Mutlu Int. J. Adv. Eng. Pure Sci 32, 145-151, 2020 | 5 | 2020 |
| Hybrid modelling of a batch separation process U Di Caprio, M Wu, F Elmaz, Y Wouters, N Vandervoort, A Anwar, ... Computers & Chemical Engineering 177, 108319, 2023 | 3 | 2023 |
| Reinforcement learning-based approach for optimizing solvent-switch processes F Elmaz, U Di Caprio, M Wu, Y Wouters, G Van Der Vorst, N Vandervoort, ... Computers & Chemical Engineering 176, 108310, 2023 | 2 | 2023 |
| Simulation and quantitative analysis of Raman spectra in chemical processes with autoencoders M Wu, U Di Caprio, O Van Der Ha, B Metten, D De Clercq, F Elmaz, ... Chemometrics and Intelligent Laboratory Systems 248, 105119, 2024 | | 2024 |
| Artificial Intelligence for industrial process control: modeling, optimization and explainability F Elmaz University of Antwerp, 2024 | | 2024 |
| A Comparative Study of Data-driven Offline Reinforcement Learning for Fed-batch Process Control O Sobhani, F Elmaz, M Robeyn, J Van den Hauwe, SP Gerdposhteh, ... Computer Aided Chemical Engineering 53, 3157-3162, 2024 | | 2024 |
| SI-M/O: Swarm Intelligence-based Modeling and Optimization of complex synthesis reaction processes M Wu, U Di Caprio, F Elmaz, F Vermeire, B Metten, O Van Der Ha, ... Computers & Chemical Engineering 179, 108431, 2023 | | 2023 |
| SI-M/O: Swarm Intelligence-based Modelling and Optimisation of complex reaction processes M Wu, U Di Caprio, F Elmaz, F Vermeire, D De Clercq, O Van Der Ha, ... 8th European Process Intensification Conference (EPIC2023), Date: 2023/05/31 …, 2023 | | 2023 |
| Transfer Learning-based Hybrid Modeling Approach for Indoor Temperature Modeling F Elmaz, S Ghane, T Huybrechts, A Anwar, S Mercelis, P Hellinckx IECON 2022–48th Annual Conference of the IEEE Industrial Electronics Society …, 2022 | | 2022 |
| A Hybrid Predictive Modelling Approach for Catalyzed Polymerization Reactors O Sobhani, H Toliati, F Elmaz, S Pormoradi Gerdposhteh, B Carius, ... Available at SSRN 4887382, 0 | | |
