Abstract
This paper aims to present a trilinear neural network method on the basis of the trilinear form of a (3+1)-dimensional \({\bar{p}}\)-GBS equation. This method can be used to construct new exact traveling wave solutions. We set the hidden neurons in three types of tensor functions to some specific functions, and reach a class of periodic bright–dark soliton solutions, two types of breather-like wave solutions and three types of rogue wave solutions for \({\bar{p}}\)-GBS equation successfully. The 3-D and density graphs of those solutions obtained are given to interpret the dynamic characteristics.
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Acknowledgements
The work was supported in part by the National Natural Science Foundation of China through grant No. 12172333, the Natural Science Foundation of Zhejiang through grant No. LY20A020003, the Key Scientific and Technological Project of Henan Province (Grant Nos. 212102210324 and 212102210432), and the Postdoctoral Research Foundation of China through grant No. ZC304122901.
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Gai, L., Qian, Y., Qin, Y. et al. Periodic bright–dark soliton, breather-like wave and rogue wave solutions to a \({\bar{p}}\)-GBS equation in (3+1)-dimensions. Nonlinear Dyn 111, 15335–15346 (2023). https://doi.org/10.1007/s11071-023-08628-y
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DOI: https://doi.org/10.1007/s11071-023-08628-y