PM2. 5 air pollution prediction through deep learning using meteorological, vehicular, and emission data: A case study of New Delhi, India D Shakya, V Deshpande, MK Goyal, M Agarwal Journal of Cleaner Production 427, 139278, 2023 | 21 | 2023 |
Predicting total sediment load transport in rivers using regression techniques, extreme learning and deep learning models D Shakya, V Deshpande, B Kumar, M Agarwal Artificial Intelligence Review 56 (9), 10067-10098, 2023 | 16 | 2023 |
Standalone and ensemble-based machine learning techniques for particle Froude number prediction in a sewer system D Shakya, V Deshpande, M Agarwal, B Kumar Neural Computing and Applications 34 (18), 15481-15497, 2022 | 16 | 2022 |
Estimating particle froude number of sewer pipes by boosting machine-learning models D Shakya, M Agarwal, V Deshpande, B Kumar Journal of Pipeline Systems Engineering and Practice 13 (2), 04022012, 2022 | 15 | 2022 |
Performance evaluation of machine learning algorithms for the prediction of particle Froude number (Frn) using hyper-parameter optimizations techniques D Shakya, V Deshpande, MJS Safari, M Agarwal Expert Systems with Applications 256, 124960, 2024 | 4 | 2024 |
Closure to “Estimating Particle Froude Number of Sewer Pipes by Boosting Machine-Learning Models” D Shakya, M Agarwal, V Deshpande, B Kumar Journal of Pipeline Systems Engineering and Practice 15 (1), 07023005, 2024 | | 2024 |
A Deep Learning Based Model to Predict PM₁₀ Concentration D Shakya, V Deshpande, M Agarwal 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine …, 2022 | | 2022 |
Data-Driven Approaches for Estimation of Particle Froude Number in a Sewer System D Shakya, M Agarwal, V Deshpande, B Kumar International Conference on Hydraulics, Water Resources and Coastal …, 2021 | | 2021 |