Hy23333/PFNN
Official implementation of Learning Dissipative Chaos In A Linear Way
This tool helps scientists and engineers predict the long-term statistical behavior of complex, turbulent systems like weather patterns or fluid dynamics. It takes observed data from a chaotic system over time and provides more accurate, stable forecasts of its future states and underlying statistical properties. Researchers and modelers working with systems that exhibit chaotic behavior would use this.
No commits in the last 6 months.
Use this if you need to understand the long-term, statistically probable behavior of chaotic systems, rather than just short-term, precise predictions.
Not ideal if your primary goal is highly accurate, short-term point predictions for non-chaotic or less complex systems.
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15
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4
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Feb 06, 2025
Commits (30d)
0
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