2025
Collocation point strategies in physics-informed neural networks: A comparative study on the Burgers' equation
This study examines the influence of six collocation point sampling strategies—random uniform, uniform grid, Latin hypercube sampling, Sobol sequence, staggered triangular lattice, and a hybrid combined approach—on the performance of PINNs applied to the one-dimensional Burgers’ equation.
Ruslan Krasnozhonov, M. Nurtas, Zh. M. Kadirbayeva et al.
· AI@DTESI · 0 citations