| A novel random walk grey wolf optimizer S Gupta, K Deep Swarm and evolutionary computation 44, 101-112, 2019 | 332 | 2019 |
| A hybrid self-adaptive sine cosine algorithm with opposition based learning S Gupta, K Deep Expert Systems with Applications 119, 210-230, 2019 | 245 | 2019 |
| Improved sine cosine algorithm with crossover scheme for global optimization S Gupta, K Deep Knowledge-Based Systems 165, 374-406, 2019 | 168 | 2019 |
| A memory-based grey wolf optimizer for global optimization tasks S Gupta, K Deep Applied Soft Computing 93, 106367, 2020 | 121 | 2020 |
| A modified sine cosine algorithm with novel transition parameter and mutation operator for global optimization S Gupta, K Deep, S Mirjalili, JH Kim Expert Systems with Applications 154, 113395, 2020 | 107 | 2020 |
| An aggregative learning gravitational search algorithm with self-adaptive gravitational constants Z Lei, S Gao, S Gupta, J Cheng, G Yang Expert Systems with Applications 152, 113396, 2020 | 96 | 2020 |
| Harmonized salp chain-built optimization S Gupta, K Deep, AA Heidari, H Moayedi, H Chen Engineering with Computers 37, 1049-1079, 2021 | 93 | 2021 |
| Opposition-based learning Harris hawks optimization with advanced transition rules: Principles and analysis S Gupta, K Deep, AA Heidari, H Moayedi, M Wang Expert Systems with Applications 158, 113510, 2020 | 93 | 2020 |
| An efficient equilibrium optimizer with mutation strategy for numerical optimization S Gupta, K Deep, S Mirjalili Applied Soft Computing 96, 106542, 2020 | 87 | 2020 |
| Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems S Gupta, H Abderazek, BS Yıldız, AR Yildiz, S Mirjalili, SM Sait Expert Systems with Applications 183, 115351, 2021 | 85 | 2021 |
| A memory guided sine cosine algorithm for global optimization S Gupta, K Deep, AP Engelbrecht Engineering Applications of Artificial Intelligence 93, 103718, 2020 | 81 | 2020 |
| Sine cosine grey wolf optimizer to solve engineering design problems S Gupta, K Deep, H Moayedi, LK Foong, A Assad Engineering with Computers 37, 3123-3149, 2021 | 73 | 2021 |
| A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons S Gupta, K Deep Applied intelligence 50 (4), 993-1026, 2020 | 70 | 2020 |
| Enhanced leadership-inspired grey wolf optimizer for global optimization problems S Gupta, K Deep Engineering with Computers 36, 1777-1800, 2020 | 59 | 2020 |
| Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation S Gupta, K Deep Neural Computing and Applications 32, 9521-9543, 2020 | 57 | 2020 |
| Predicting permeability of tight carbonates using a hybrid machine learning approach of modified equilibrium optimizer and extreme learning machine N Kardani, A Bardhan, S Gupta, P Samui, M Nazem, Y Zhang, A Zhou Acta Geotechnica, 1-17, 2021 | 53 | 2021 |
| An opposition-based chaotic grey wolf optimizer for global optimisation tasks S Gupta, K Deep Journal of Experimental & Theoretical Artificial Intelligence 31 (5), 751-779, 2019 | 48 | 2019 |
| Random walk grey wolf optimizer for constrained engineering optimization problems S Gupta, K Deep Computational Intelligence 34 (4), 1025-1045, 2018 | 35 | 2018 |
| Cauchy grey wolf optimiser for continuous optimisation problems S Gupta, K Deep Journal of Experimental & Theoretical Artificial Intelligence 30 (6), 1051-1075, 2018 | 34 | 2018 |
| Hybrid grey wolf optimizer with mutation operator S Gupta, K Deep Soft Computing for Problem Solving: SocProS 2017, Volume 2, 961-968, 2019 | 29 | 2019 |
Kusum DeepProfessor, Department of Mathematics, Indian Institute of Technology RoorkeeVerified email at iitr.ernet.in
