Multi-output physics-informed neural network for one- and two-dimensional nonlinear time distributed-order models

In this article, a physics-informed neural network based on the time difference method is developed to solve one-dimensional (1D) and two-dimensional (2D) nonlinear time distributed-order models. The FBN-$ \theta $, which is constructed by combining the fractional second order backward difference fo...

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