| Autor: |
Jian-Guo Liu, Wen-Hui Zhu, Ya-Kui Wu, Guo-Hua Jin |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Results in Physics, Vol 47, Iss , Pp 106341- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2211-3797 |
| DOI: |
10.1016/j.rinp.2023.106341 |
| Popis: |
In this work, a multivariate bilinear neural network method is proposed to seek more exact analytical solutions of nonlinear partial differential equations. As an example, the (2+1)-dimensional fractional generalized Calogero–Bogoyavlensky–Schiff–Bogoyavlensky–Konopelchenko equation is investigated via selecting the 3-2-2-1, 3-2-3-1 and 3-3-2-1 models, respectively. The exact analytical solutions with several arbitrary activation functions are derived and the dynamics properties are shown in some three-dimensional and density maps by choosing different activation functions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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