| A novel hybrid optimization methodology to optimize the total number and placement of wind turbines P Mittal, K Kulkarni, K Mitra Renewable energy 86 (https://doi.org/10.1016/j.renene.2015.07), 133-147, 2016 | 81 | 2016 |
| Comparative study of surrogate approaches while optimizing computationally expensive reaction networks SS Miriyala, P Mittal, S Majumdar, K Mitra Chemical Engineering Science 140 (https://doi.org/10.1016/j.ces.2015.09.03 …, 2016 | 75 | 2016 |
| Kriging surrogate based multi-objective optimization of bulk vinyl acetate polymerization with branching A Mogilicharla, P Mittal, S Majumdar, K Mitra Materials and Manufacturing Processes 30 (4), 394-402, 2015 | 58 | 2015 |
| Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach P Mittal, K Mitra, K Kulkarni Energy conversion and management 132, 147-160, 2017 | 44 | 2017 |
| Determining layout of a wind farm with optimal number of turbines: A decomposition based approach P Mittal, K Mitra Journal of cleaner production 202, 342-359, 2018 | 23 | 2018 |
| Better wind forecasting using evolutionary neural architecture search driven green deep learning KN Pujari, SS Miriyala, P Mittal, K Mitra Expert Systems with Applications 214, 119063, 2023 | 21 | 2023 |
| In search of flexible and robust wind farm layouts considering wind state uncertainty P Mittal, K Mitra Journal of cleaner production 248, 119195, 2020 | 20 | 2020 |
| Many-objective optimization of hot-rolling process of steel: A hybrid approach P Mittal, I Mohanty, A Malik, K Mitra Materials and Manufacturing Processes 35 (6), 668-676, 2020 | 16 | 2020 |
| Decomposition based multi-objective optimization to simultaneously determine the number and the optimum locations of wind turbines in a wind farm P Mittal, K Mitra IFAC-PapersOnLine 50 (1), 159-164, 2017 | 11 | 2017 |
| A novel and efficient hybrid optimization approach for wind farm micro-siting P Mittal, K Kulkarni, K Mitra IFAC-PapersOnLine 48 (8), 397-402, 2015 | 8 | 2015 |
| Multi-objective optimization of energy generation and noise propagation: A hybrid approach P Mittal, K Kulkarni, K Mitra 2016 Indian Control Conference (ICC), 499-506, 2016 | 6 | 2016 |
| A tanks-in-series approach to estimate parameters for lithium-ion battery models S Kolluri, P Mittal, A Subramaniam, Y Preger, V De Angelis, ... Journal of The Electrochemical Society 169 (5), 050525, 2022 | 4 | 2022 |
| Energy-noise trade-off to optimize the total number and the placement of wind turbines on wind farms: A hybrid approach P Mittal, K Mitra 2017 Indian Control Conference (ICC), 129-136, 2017 | 4 | 2017 |
| A fast and effective algorithm to optimize the total number and placement of wind turbines K Kulkarni, P Mittal 2014 IEEE Global Humanitarian Technology Conference-South Asia Satellite …, 2014 | 4 | 2014 |
| Micrositing under practical constraints addressing the energy‐noise‐cost trade‐off P Mittal, K Mitra Wind Energy 23 (10), 1905-1918, 2020 | 3 | 2020 |
| Optimal Long Short Term Memory Networks for long-term forecasting of real wind characteristics KN Pujari, SS Miriyala, P Mittal, K Mitra IFAC-PapersOnLine 53 (1), 648-653, 2020 | 3 | 2020 |
| Determination of optimal layout of wind turbines inside a wind farm in presence of practical constraints P Mittal, K Mitra 2019 fifth Indian control conference (ICC), 353-358, 2019 | 3 | 2019 |
| On determining optimal number and layout of wind turbines using space decomposed cost-energy trade-off algorithm P Mittal, K Mitra 2018 Indian Control Conference (ICC), 149-154, 2018 | 3 | 2018 |
| Efficient Wind Farm Micro-siting using Novel Optimization Approaches P Mittal, K Mitra Indian Institute of Technology Hyderabad, 2020 | 2 | 2020 |
| Comparative Study of Multi/Many-Objective Evolutionary Algorithms on Hot Rolling Application P Mittal, A Malik, I Mohanty, K Mitra Optimization in Industry: Present Practices and Future Scopes, 331-349, 2019 | 2 | 2019 |
Kishalay MitraProfessor, Indian Institute of Technology HyderabadVerified email at iith.ac.in
