Published October 30, 2024 | Version v3

Time series of chaotic systems

Authors/Creators

  • 1. Arizona State University

Description

 

Long time series of chaotic systems, all three-dimensional. Can be used in short- and long-term forecasting, reconstruction, etc.

Codes in GitHub: https://github.com/Zheng-Meng/Dynamics-Reconstruction-ML.

We used the dataset in dynamics reconstruction from sparse observations with no training on target systems:

Zhai, Zheng-Meng, Jun-Yin Huang, Benjamin D. Stern, and Ying-Cheng Lai. "Reconstructing dynamics from sparse observations with no training on target system." arXiv preprint arXiv:2410.21222 (2024).

In addition, two folders with additional data, data_response, which is generated by dysts (https://github.com/williamgilpin/dysts) and data_nonautonomous, are provided for further evaluation of the dynamics reconstruction framework.

 

Files

data_nonautonomous.zip

Files (5.3 GB)

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