Application and evaluation of random forest classifier technique for fault detection in bioreactor operation R Shrivastava, H Mahalingam, NN Dutta Chemical Engineering Communications 204 (5), 591-598, 2017 | 44 | 2017 |
Comparative study of boosting and bagging based methods for fault detection in a chemical process R Shrivastava 2021 International Conference on Artificial Intelligence and Smart Systems …, 2021 | 3 | 2021 |
Modeling of Surfactant-Enhanced Drying of Poly(styrene)-p-xylene Polymeric Coatings Using Machine Learning Technique RK Arya, J Sharma, R Shrivastava, D Thapliyal, GD Verros coatings 11 (12), 1529, 2021 | 3 | 2021 |
Selective Oxidation of Toluene to Benzaldehyde using Cu/Sn/Br Catalyst System K Rajurkar, N Kulkarni, V Rane, R Shrivastava Int J Chem Sci 9 (2), 545-52, 2011 | 2 | 2011 |
Modeling of Triphenyl Phosphate Surfactant Enhanced Drying of Polystyrene/p-Xylene Coatings Using Artificial Neural Network D Thapliyal, R Shrivastava, GD Verros, S Verma, RK Arya, P Sen, ... Processes 12 (2), 260, 2024 | | 2024 |
Advanced Approach towards Zero Waste: Modeling of Copper Recovery from e-Waste by Using Machine Learning Technique SK Srivastava, RK Shrivastava | | 2023 |
Performance Assessment of Ensemble Decision Tree-based Fault Detection System in a Chemical Process R Shrivastava, KN Gupta, NN Dutta International Journal of Applied Engineering Research 13 (9), 7190-7196, 2018 | | 2018 |
Optimum Parameters for Fault Detection in Bioreactor Using Support Vector Machine and Neural Network R Shrivastava, H Mahalingam, NN Dutta International Journal for Research in Applied Science & Engineering …, 2017 | | 2017 |