3 citations · 4 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2023
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization
Niranjan Sitapure, Joseph S Kwon
Most existing digital twins rely on data-driven black-box models, predominantly using deep neural recurrent, and convolutional neural networks (DNNs, RNNs, and CNNs) to capture the…
eess.SY2023★ 3 cited
Require Process Control? LSTMc is all you need!
Niranjan Sitapure, Joseph S Kwon
Over the past three decades, numerous controllers have been developed to regulate complex chemical processes, but they have certain limitations. Traditional PI/PID controllers ofte…
cond-mat.mtrl-sci2023★ 1 cited
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers
Niranjan Sitapure, Joseph S. Kwon
For prediction and real-time control tasks, machine-learning (ML)-based digital twins are frequently employed. However, while these models are typically accurate, they are custom-d…