| Development of a recurrent neural networks-based NMPC for controlling the concentration of a crystallization process FARD Lima, MGF de Moraes, AR Secchi, MB de Souza Jr Digital Chemical Engineering 5, 100052, 2022 | 18 | 2022 |
| Improved modeling of crystallization processes by Universal Differential Equations FARD Lima, CM Rebello, EA Costa, VV Santana, MGF de Moares, ... Chemical Engineering Research and Design 200, 538-549, 2023 | 9 | 2023 |
| Modeling and Predictive Control of Cooling Crystallization of Potassium Sulfate by Dynamic Image Analysis: Exploring Phenomenological and Machine Learning Approaches MGF de Moraes, FARD Lima, PLC Lage, MB de Souza Jr, AG Barreto Jr, ... Industrial & Engineering Chemistry Research 62 (24), 9515-9532, 2023 | 8 | 2023 |
| A recurrent neural networks-based approach for modeling and control of a crystallization process FARD Lima, GFM de Miranda, MGF de Moraes, BDO Capron, ... Computer Aided Chemical Engineering 51, 1423-1428, 2022 | 5 | 2022 |
| An NN-NMPC for Controlling a Crystallization Process in the Saturated and Undersaturated Zones FARD Lima, MGF de Moraes, AG Barreto, AR Secchi, MB de Souza Jr Computer Aided Chemical Engineering 52, 1835-1840, 2023 | 3 | 2023 |
| Controlling Paracetamol Unseeded Batch Crystallization with NMPC and Inverse Model FARD Lima, MGF de Moraes, MA Grover, AG Barreto, AR Secchi, ... IFAC-PapersOnLine 58 (14), 31-36, 2024 | 2 | 2024 |
| Statistical Analyses of a Population Balance Model of a Batch Crystallization Process FARD Lima, G Barreto Correa, MGF de Moraes, ISV Segtovich, ... Crystal Growth & Design 24 (1), 308-324, 2023 | 2 | 2023 |
| Influence of Estimators and Numerical Approaches on the Implementation of NMPCs FARD Lima, RR Faria, R Curvelo, MCF Cadorini, CAG Echeverry, ... Processes 11 (4), 1102, 2023 | 2 | 2023 |
| Neural Network Inverse Model Controllers for Paracetamol Unseeded Batch Cooling Crystallization FARD Lima, MGF de Moraes, MA Grover, AG Barreto Junior, AR Secchi, ... Industrial & Engineering Chemistry Research 63 (45), 19613-19627, 2024 | 1 | 2024 |
| Applications of machine learning for modeling and advanced control of crystallization processes: Developments and perspectives FARD Lima, MGF de Moraes, AG Barreto Jr, AR Secchi, MA Grover, ... Digital Chemical Engineering, 100208, 2024 | | 2024 |
| A parallel hybrid model for integrating protein adsorption models with deep neural networks M de Souza Gama, FARD Lima, VV Santana, IB dos Reis Nogueira, ... Adsorption 30 (5), 473-488, 2024 | | 2024 |
| Enhanced Hybrid Model for Gas-Lifted Oil Production RR Faria, FARD Lima, AR Secchi, MB de Souza IFAC-PapersOnLine 58 (14), 7-12, 2024 | | 2024 |
| A Parallel Hybrid Model for Integrating Protein Adsorption Models with Deep Neural Networks MSG Gama, FARDL Lima, VVS Santana, IBRN Nogueira, FWT Tavares, ... | | 2023 |
| The Relationship between Diffusion Coefficient and Ion Conductivity in Solid-State Electrolytes Using Feedforward Neural Networks and Symbolic Regression I Ito Iwakiri, JV Silva, N Delgado, F Lima, C Rebello, ... Available at SSRN 5101259, 0 | | |
| Avaliação da ecoeficiência e da intensificação do processo de separação metilal-metanol via simulação computacional BMM Rozalino, BPC Novaes, FARD Lima | | |
Maurício B de Souza Jr.School of Chemistry, UFRJVerified email at eq.ufrj.br
