Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866912024013832192 |
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| author | Sakaguchi, Hidetsugu |
| author_facet | Sakaguchi, Hidetsugu |
| contents | Several authors have reported that the echo state network reproduces bifurcation diagrams of some nonlinear differential equations using the data for a few control parameters. We demonstrate that a simpler feedforward neural network can also reproduce the bifurcation diagram of the logistics map and synchronization transition in globally coupled Stuart-Landau equations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_07468 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks Sakaguchi, Hidetsugu Chaotic Dynamics Neural and Evolutionary Computing Adaptation and Self-Organizing Systems Several authors have reported that the echo state network reproduces bifurcation diagrams of some nonlinear differential equations using the data for a few control parameters. We demonstrate that a simpler feedforward neural network can also reproduce the bifurcation diagram of the logistics map and synchronization transition in globally coupled Stuart-Landau equations. |
| title | Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks |
| topic | Chaotic Dynamics Neural and Evolutionary Computing Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2409.07468 |