Interaction phenomenon for variable coefficient Kadomtsev-Petviashvili equation by utilizing variable coefficient bilinear neural network method

Autor:	Liu, Jian-Guo, Zhu, Wen-Hui
Rok vydání:	2022
Předmět:	Nonlinear Sciences - Exactly Solvable and Integrable Systems Mathematical Physics Nonlinear Sciences - Pattern Formation and Solitons
Druh dokumentu:	Working Paper
Popis:	In this paper, a variable coefficient Bilinear neural network method is proposed to deal with the analytical solutions of variable coefficient nonlinear partial differential equations. As an example, a Kadomstev-Petviashvili equation with variable coefficients is investigated by using the variable coefficient Bilinear neural network method. By establishing "3-2-2-1" and "3-3-2-1" models respectively, rich analytical solutions of the variable coefficient Kadomstev-Petviashvili equation are obtained. By choosing some special values of the parameters, the dynamics properties are demonstrated in some three-dimensional and density graphics. Comment: 11 pages, 17 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2301.10069 Zobrazit plný text záznamu View this record from Arxiv