0000-0002-3060-9285 Employment
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Publications (9)
- Performance evaluation of machine learning algorithms for the prediction of particle Froude number (Frn) using hyper-parameter optimizations techniques Save
- Closure to "estimating Particle Froude Number of Sewer Pipes by Boosting Machine-Learning Models" Save
- Smart Meter Data Analytics for Residential Consumers Save
- Data-Driven Approaches for Estimation of Particle Froude Number in a Sewer System Save
- PM2.5 air pollution prediction through deep learning using meteorological, vehicular, and emission data: A case study of New Delhi, India Save
- Predicting total sediment load transport in rivers using regression techniques, extreme learning and deep learning models Save
- A Deep Learning Based Model to Predict PM Concentration Save
- Estimating Particle Froude Number of Sewer Pipes by Boosting Machine-Learning Models Save
- Standalone and ensemble-based machine learning techniques for particle Froude number prediction in a sewer system Save