| 1 |
Deep learning based system identification of industrial integrated grinding circuits
Miriyala SS, Mitra K
Powder Technology, 360, 921, 2020 |
| 2 |
Data-driven multi-objective predictive control of offshore wind farm based on evolutionary optimization
Yin XX, Zhang WC, Jiang ZS, Pan L
Renewable Energy, 160, 974, 2020 |
| 3 |
Data-driven surrogate assisted evolutionary optimization of hybrid powertrain for improved fuel economy and performance
Bhattacharjee D, Ghosh T, Bhola P, Martinsen K, Dan PK
Energy, 183, 235, 2019 |
| 4 |
An innovative multi-objective optimization approach for long-term energy planning
Mahbub MS, Viesi D, Cattani S, Crema L
Applied Energy, 208, 1487, 2017 |
| 5 |
Dynamic Modeling and Metabolic Flux Analysis for Optimized Production of Rhamnolipids
Eswari JS, Venkateswarlu C
Chemical Engineering Communications, 203(3), 326, 2016 |
| 6 |
Improving evolutionary algorithm performance for integer type multi-objective building system design optimization
Xu WL, Chong A, Karaguzel OT, Lam KP
Energy and Buildings, 127, 714, 2016 |
| 7 |
Design of Hybrid Distillation/Melt Crystallization Processes for Separation of Close-Boiling Mixtures
Micovic J, Beierling T, Lutze P, Sadowski G, Gorak A
Chemie Ingenieur Technik, 84(11), 2035, 2012 |
| 8 |
Using fuzzy logic to tune an evolutionary algorithm for dynamic optimization of chemical processes
Pham QT
Computers & Chemical Engineering, 37, 136, 2012 |
| 9 |
Generator approach to evolutionary optimization of catalysts and its integration with surrogate modeling
Holena M, Linke D, Rodemerck U
Catalysis Today, 159(1), 84, 2011 |
| 10 |
An execution, monitoring and replanning approach for optimal energy management in microgrids
Sanseverino ER, Di Silvestre ML, Ippolito MG, De Paola A, Lo Re G
Energy, 36(5), 3429, 2011 |
