1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.NE2023★ 1 cited
Training Physics-Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction
Bo Wang, A. K. Qin, Sajjad Shafiei +3
Physics-informed neural networks (PINNs) are a newly emerging research frontier in machine learning, which incorporate certain physical laws that govern a given data set, e.g., tho…
physics.soc-ph2022
Traffic disruption modelling with mode shift in multi-modal networks
Dong Zhao, Adriana-Simona Mihaita, Yuming Ou +6
A multi-modal transport system is acknowledged to have robust failure tolerance and can effectively relieve urban congestion issues. However, estimating the impact of disruptions a…