| Lessons learned in transforming from traditional to agile development N Ganesh | 71 | 2012 |
| Random forest regression-based machine learning model for accurate estimation of fluid flow in curved pipes P Jain, A Choudhury, P Dutta, K Kalita, P Barsocchi Processes 9 (11), 2095, 2021 | 49 | 2021 |
| Efficient feature selection using weighted superposition attraction optimization algorithm N Ganesh, R Shankar, R Čep, S Chakraborty, K Kalita Applied Sciences 13 (5), 3223, 2023 | 47 | 2023 |
| A study on image processing with data analysis DC Prakash, RC Narayanan, N Ganesh, M Ramachandran, ... AIP Conference Proceedings 2393 (1), 2022 | 43 | 2022 |
| Robust metamodels for accurate quantitative estimation of turbulent flow in pipe bends N Ganesh, P Dutta, M Ramachandran, AK Bhoi, K Kalita Engineering with Computers 36 (3), 1041-1058, 2020 | 40 | 2020 |
| A novel decomposition-based multi-objective symbiotic organism search optimization algorithm N Ganesh, R Shankar, K Kalita, P Jangir, D Oliva, M Pérez-Cisneros Mathematics 11 (8), 1898, 2023 | 32 | 2023 |
| An intelligent predictive model-based multi-response optimization of EDM process N Ganesh, RK Ghadai, AK Bhoi, K Kalita, XZ Gao Computer Modeling in Engineering & Sciences 124 (2), 459-476, 2020 | 28 | 2020 |
| Performance evaluation of depth adjustment and void aware pressure routing (DA-VAPR) protocol for underwater wireless sensor networks N Ganesh The Computer Journal 63 (2), 193-202, 2020 | 28 | 2020 |
| Movie recommender systems: Concepts, methods, challenges, and future directions S Jayalakshmi, N Ganesh, R Čep, J Senthil Murugan Sensors 22 (13), 4904, 2022 | 22 | 2022 |
| Hybridized particle swarm—Gravitational search algorithm for process optimization R Shankar, N Ganesh, R Čep, RC Narayanan, S Pal, K Kalita Processes 10 (3), 616, 2022 | 20 | 2022 |
| Multi-Objective High-Fidelity Optimization Using NSGA-III and MO-RPSOLC. N Ganesh, U Ragavendran, K Kalita, P Jain, XZ Gao CMES-Computer Modeling in Engineering & Sciences 129 (2), 2021 | 19 | 2021 |
| PSO-tuned support vector machine metamodels for assessment of turbulent flows in pipe bends G Narayanan, M Joshi, P Dutta, K Kalita Engineering Computations 37 (3), 981-1001, 2020 | 19 | 2020 |
| Gated deep reinforcement learning with red deer optimization for medical image classification N Ganesh, S Jayalakshmi, R Narayanan, M Mahdal, HM Zawbaa, ... IEEE Access, 2023 | 17 | 2023 |
| Insights on Various Meeting Requisites in Handling Agile Projects: Shared Experiences From Indian Software Organizations N Ganesh Asian Journal of Information Technology 15 (21), 4302-4308, 2016 | 16 | 2016 |
| A novel many-objective sine–cosine algorithm (MAOSCA) for engineering applications RC Narayanan, N Ganesh, R Čep, P Jangir, JS Chohan, K Kalita Mathematics 11 (10), 2301, 2023 | 15 | 2023 |
| Issues identified in the software process due to barriers found during eliciting requirements on agile software projects: Insights from India N Ganesh, S Thangasamy International Journal of Computer Applications 16 (5), 7-12, 2011 | 14 | 2011 |
| Zawbaa, and Mohamed Ali,“ N Ganesh, S Jayalakshmi, RC Narayanan, M Mahdal Gated Deep Reinforcement Learning with Red deer Optimization for Medical …, 2023 | 13 | 2023 |
| New agile testing modes N Ganesh, S Thangasamy Information Technology Journal 11 (6), 707, 2012 | 6 | 2012 |
| Theoretical insights on e-government and global trends in e-governance technologies & applications N Ganesh, B Premkumar, K Priya International Journal of Engineering and Advanced Technology 8 (5), 1843-1850, 2019 | 5 | 2019 |
| Challenges Faced in the Enterprise Resource Planning Material Management Section when Transitioning Towards Agile Software Development N Ganesh, RC Narayanan International Journal of Engineering and Advanced Technology 8 (6), 3472-3475, 2019 | 3 | 2019 |
Kanak KalitaVel Tech University, Avadi, India | (Top 2% Scientist)Verified email at veltech.edu.in
