Generalized lump solutions, classical lump solutions and rogue waves of the (2+1)-dimensional Caudrey-Dodd-Gibbon-Kotera-Sawada-like equation

•The lump solution method is generalized.•The CDGKS-like equation is derived through the generalized bilinear method.•The new rogue wave solution is constructed by using “3-2-2” neural network model. Under investigation in this paper is the (2+1)-dimensional Caudrey-Dodd-Gibbon-Kotera-Sawada-like (C...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Applied mathematics and computation Ročník 403; s. 126201
Hlavní autoři: Zhang, Run-Fa, Li, Ming-Chu, Albishari, Mohammed, Zheng, Fu-Chang, Lan, Zhong-Zhou
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 15.08.2021
Témata:
Bilinear neural network method
CDGKS-Like equation
Generalized bilinear transformation
Bilinear neural network method
Generalized bilinear transformation
CDGKS-Like equation
ISSN:0096-3003
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:•The lump solution method is generalized.•The CDGKS-like equation is derived through the generalized bilinear method.•The new rogue wave solution is constructed by using “3-2-2” neural network model. Under investigation in this paper is the (2+1)-dimensional Caudrey-Dodd-Gibbon-Kotera-Sawada-like (CDGKS-like) equation. Based on bilinear neural network method, the generalized lump solution, classical lump solution and the novel analytical solution are constructed by giving some specific activation functions in the single hidden layer neural network model and the “3-2-2” neural network model. By means of symbolic computation, these analytical solutions and corresponding rogue waves are obtained with the help of Maple software. These results fill the blank of the CDGKS-like equation in the existing literature. Via various three-dimensional plots, curve plots, density plots and contour plots, dynamical characteristics of these waves are exhibited. The effective methods used in this paper is helpful to study the nonlinear evolution equations in plasmas, mathematical physics, electromagnetism and fluid dynamics.
ISSN:0096-3003
DOI:10.1016/j.amc.2021.126201