Dear Colleagues,

PDEs have a wide application background, such as economic problems, engineering problems, financial models, power systems, etc. Thus, it is interesting work to find good methods for PDE problems. However, effective methods for PDE problems are not easy to design, especially for some complex problems with a practical background. Numerical methods are often used. It well known that machine learning is regarded as one of the effective methods for many problems, especially for some difficult problems. We can ensure that there must exist good relation and some rules by using the idea of the machine learning and its some techniques for nonlinear PDEs and symmetry.

Submit your paper and select the Journal “Symmetry” and the Special Issue “Nonlinear PDEs and Symmetry” via: MDPI submission system. Our papers will be published on a rolling basis and we will be pleased to receive your submission once you have finished it.

Prof. Dr. Gonglin Yuan
Dr. Maojun Zhang
Guest Editors

Manuscript Submission Information

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• nonlinear PDEs
• symmetry
• machine learning
• numerical methods
• convergence