Use of BNNM for interference wave solutions of the gBS-like equation and comparison with PINNs. (arXiv:2210.12154v1 [cs.LG])

In this work, the generalized broken soliton-like (gBS-like) equation is
derived through the generalized bilinear method. The neural network model,
which can fit the explicit solution with zero error, is found. The interference
wave solution of the gBS-like equation is obtained by using the bilinear neural
network method (BNNM) and physical informed neural networks (PINNs).
Interference waves are shown well via three-dimensional plots and density
plots. Compared with PINNs, the bilinear neural network method is not only more
accurate but also faster.



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