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Nonlinear Engineering

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JOURNAL INFORMATION
Publisher de Gruyter
Open Access NO
Quartile Q2
Citation Count 460
P-ISSN 2192-8029
E-ISSN 2192-8010
Categories Chemical Engineering (miscellaneous), Computer Networks and Communications, Engineering (miscellaneous), Modeling and Simulation
Area Chemical Engineering, Computer Science, Engineering, Mathematics
Region Western Europe
Country Germany
Summary

  1. Nonlinear Engineering is published by de Gruyter
  2. It is not an oppen access journal
  3. The Subject Area : Chemical Engineering; Computer Science; Engineering; Mathematics

Latest Articles published

Last updated: 20/11/2024

Global well-posedness and exponential decay estimates for semilinear Newell–Whitehead–Segel equation


Last updated: 20/11/2024

Mathematical model based on nonlinear differential equations and its control algorithm


Last updated: 20/11/2024

Petrov-Galerkin method for small deflections in fourth-order beam equations in civil engineering


Last updated: 04/11/2024

Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system


Last updated: 04/11/2024

Analysis of the magnetohydrodynamic effects on non-Newtonian fluid flow in an inclined non-uniform channel under long-wavelength, low-Reynolds number conditions


Last updated: 04/11/2024

Convergence analysis of non-matching finite elements for a linear monotone additive Schwarz scheme for semi-linear elliptic problems


Last updated: 21/10/2024

Novel dynamics of the fractional KFG equation through the unified and unified solver schemes with stability and multistability analysis


Last updated: 21/10/2024

Experimental and numerical investigations into torsional-flexural behaviours of railway composite sleepers and bearers


Last updated: 21/10/2024

Computational analysis of the Covid-19 model using the continuous Galerkin–Petrov scheme


Last updated: 21/10/2024

Retraction of “Convolutional neural network for UAV image processing and navigation in tree plantations based on deep learning”