Evidence map›Paper›PMID 41023091›Full record

ArticleScientific reports2025

Wave modelling of 3 + 1 dimensional Wazwaz Kaur Boussinesq equation with the bilinear neural network method.

Nur Hasan Mahmud Shahen, Md Al Amin, M Monir Uddin, Foyjonnesa, M M Rahman

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nur Hasan Mahmud ShahenDepartment of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh. nhmshahen@gmail.com.
Md Al AminDepartment of Mathematics, University of Rajshahi, Rajshahi, 6305, Bangladesh.
M Monir UddinDepartment of Mathematics and Physics, North South University, Dhaka, 1229, Bangladesh.
FoyjonnesaDepartment of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
M M RahmanDepartment of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates a newly developed (3 + 1)-dimensional Wazwaz-Kaur-Boussinesq equation, a significant advancement in fluid dynamics, nonlinear wave phenomena, and mathematical physics, due to its capability to model complex wave structures across multiple spatial and temporal dimensions. By applying the bilinear neural network method to a bilinearized form of the equation with the concept of corresponding tensor formula, we introduced new activation functions in a single-layer neural configuration using a "4-2-1" neuron structure. For the very first time we combined the bilinear neural network method with the (3 + 1)-dimensional Wazwaz-Kaur-Boussinesq equation. In our proposed method, the neural setup allows the network to efficiently capture and represent the nonlinear behaviour intrinsic to multidimensional wave propagation. Using Maple software for symbolic computation techniques, we systematically obtained lump, single, and periodic soliton wave solutions in the equation, revealing the complex dynamics of waves and unique aspects of the physical behaviour of the system. Such solutions and their parameters were investigated using complex 3D, 2D, contour, and density graphs to illustrate how parameter changes influence the form and dynamical features of the wave packets. Such artworks help better explain the dynamics of the exact solution of the equation and illustrate more the system's complex dynamics and physical features.

Indexed as

Bilinear neural network methodExact solutionsMathematical physicsNonlinear PDEsSolitary wavesUniversal tensor formula

Identifiers

PMID41023091
PMCPMC12479934

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