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Through symbolic computation with Maple, fifty-seven sets of rational wave solutions to the generalized Calogero-Bogoyavlenskii-Schiff equation are presented by employing the generalized bilinear operator when the parameter p = 2 . Via the three-dimensional plots and contour plots with the help of Maple, the dynamics of these solutions are described very well. These solutions have greatly enriched the exact solutions of the generalized Calogero-Bogoyavlenskii-Schiff equation on the existing literature. The result will be widely used to describe many nonlinear scientific phenomena.

It is well known that most classical test functions to solve nonlinear partial differential equations can be constructed via single hidden layer neural network model by using Bilinear Neural Network Method (BNNM). In this paper, the neural network model of test function for the (3+1)-dimensional Jimbo–Miwa equation is extended to the “4-2-3” model. By giving some specific activation functions, new test function is constructed to obtain analytical solutions of the (3+1)-dimensional Jimbo–Miwa equation. Rogue wave solutions and the bright and dark solitons are obtained by giving some specific parameters. Via curve plots, three-dimensional plots, contour plots and density plots, dynamical characteristics of these waves are exhibited.

In this work, the [Formula: see text]-dimensional Sawada–Kotera-like (SK-like) equation is derived through the generalized bilinear equation from SK equation. By using “3-2” and “3-2-2” neural network models, three trial functions are constructed. Classic lump, generalized lump solutions and new rogue wave solutions are acquired by giving a number of specific parameters. Through a variety of curve plots of three-dimensional contour plotting, these rogue waves are intuitively displayed.

In this paper, new trial functions are constructed via extended “3-3-2-3-1” and “3-3-2-3-2-1” network models based on the bilinear neural networks method. The new lump-type solution, interaction solution, plentiful arbitrary function solutions and periodic lump solutions of the dimensionally reduced [Formula: see text]-generalized Burgers–Kadomtsev–Petviashvili equation are solved. To analyze the dynamic properties of the solutions, appropriate parameters and different activated functions are defined in arbitrary function solutions. Through the three-dimensional and density plots, the dynamical characteristics of the solutions are shown well.

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.