In the paper, a reduced basis (RB) method for time-dependent nonlocal problems with a special parameterized fractional Laplace kernel function is
proposed. Because of the lack of sparsity of discretized nonlocal systems compared to corresponding local partial differential equation (PDE) systems, model
reduction for nonlocal systems becomes more critical. The method of snapshots
and greedy (MOS-greedy) algorithm of RB method is developed for nonlocal
problems with random inputs, which provides an efficient and reliable approximation of the solution. A major challenge lies in the excessive influence of the
time domain on the model reduction process. To address this, the Fourier transform is applied to convert the original time-dependent parabolic equation into
a frequency-dependent elliptic equation, where variable frequencies are independent. This enables parallel computation for approximating the solution in
the frequency domain. Finally, the proposed MOS-greedy algorithm is applied
to the nonlocal diffusion problems. Numerical results demonstrate that it provides an accurate approximation of the full order problems and significantly
improves computational efficiency.
