Design of feedforward neural networks in the classification of hyperspectral imagery using superstructural optimization H Sildir, E Aydin, T Kavzoglu Remote Sensing 12 (6), 956, 2020 | 41 | 2020 |
NMPC using Pontryagin’s Minimum Principle-Application to a two-phase semi-batch hydroformylation reactor under uncertainty E Aydin, D Bonvin, K Sundmacher Computers & Chemical Engineering 108, 47-56, 2018 | 31 | 2018 |
Dynamic optimization of constrained semi-batch processes using Pontryagin’s minimum principle—An effective quasi-Newton approach E Aydin, D Bonvin, K Sundmacher Computers & Chemical Engineering 99, 135-144, 2017 | 27 | 2017 |
Optimal design and operation of a multi-energy microgrid using mixed-integer nonlinear programming: Impact of carbon cap and trade system and taxing on equipment selections H Akulker, E Aydin Applied Energy 330, 120313, 2023 | 22 | 2023 |
Physics-informed recurrent neural networks and hyper-parameter optimization for dynamic process systems T Asrav, E Aydin Computers & Chemical Engineering 173, 108195, 2023 | 21 | 2023 |
Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios SM Tatar, H Akulker, H Sildir, E Aydin International Journal of Hydrogen Energy 47 (65), 27848-27865, 2022 | 20 | 2022 |
Dynamic modeling of an industrial diesel hydroprocessing plant by the method of continuous lumping E Aydın, AD Celebi, H Sildir, Y Arkun, U Canan, G Is, M Erdogan Computers & Chemical Engineering 82, 44-54, 2015 | 20 | 2015 |
Toward fast dynamic optimization: An indirect algorithm that uses parsimonious input parameterization E Aydin, D Bonvin, K Sundmacher Industrial & Engineering Chemistry Research 57 (30), 10038-10048, 2018 | 15 | 2018 |
A Mixed-Integer linear programming based training and feature selection method for artificial neural networks using piece-wise linear approximations H Sildir, E Aydin Chemical Engineering Science 249, 117273, 2022 | 12 | 2022 |
Computationally efficient NMPC for batch and semi-batch processes using parsimonious input parameterization E Aydin, D Bonvin, K Sundmacher Journal of Process Control 66, 12-22, 2018 | 10 | 2018 |
Plant-wide optimization and control of an industrial diesel hydro-processing plant E Aydın, Y Arkun, G Is, M Mutlu, M Dikbas Computers & Chemical Engineering 87, 234-245, 2016 | 9 | 2016 |
Machine learning-enabled optimization of interstitial fluid collection via a sweeping microneedle design C Tarar, E Aydın, AK Yetisen, S Tasoglu ACS omega 8 (23), 20968-20978, 2023 | 6 | 2023 |
Optimal artificial neural network architecture design for modeling an industrial ethylene oxide plant H Sildir, S Sarrafi, E Aydin Computers & Chemical Engineering 163, 107850, 2022 | 6 | 2022 |
The problem of informed consent in children E Aydin COCUK SAGLIGI VE HASTALIKARI DERGISI 46 (2), 148-152, 2003 | 6 | 2003 |
Physics informed piecewise linear neural networks for process optimization ES Koksal, E Aydin Computers & Chemical Engineering 174, 108244, 2023 | 5 | 2023 |
Economic model predictive control (EMPC) of an industrial diesel hydroprocessing plant E Aydın, Y Arkun, G Is IFAC-PapersOnLine 49 (7), 568-573, 2016 | 5 | 2016 |
Dynamic optimization of constrained semi-batch processes using pontryagin’s minimum principle and parsimonious parameterization E Aydin, D Bonvin, K Sundmacher Computer Aided Chemical Engineering 40, 2041-2046, 2017 | 4 | 2017 |
Optimization of capacitance in supercapacitors by constructing an experimentally validated hybrid artificial neural networks-genetic algorithm framework D Kaya, D Koroglu, E Aydın, B Uralcan Journal of Power Sources 568, 232987, 2023 | 3 | 2023 |
Bayesian machine learning optimization of microneedle design for biological fluid sampling C Tarar, E Aydın, AK Yetisen, S Tasoglu Sensors & Diagnostics 2 (4), 858-866, 2023 | 3 | 2023 |
Uncertainty Propagation Based MINLP approach for artificial neural network structure reduction H Sildir, S Sarrafi, E Aydin Processes 10 (9), 1716, 2022 | 3 | 2022 |