AlexandraBaier/deepsysid
System identification toolkit for multistep prediction using deep learning and hybrid methods.
This toolkit helps engineers and scientists predict future behavior of dynamic systems based on past observations. You input time-series data from a system and a configuration file outlining different models to test. The output is a set of best-performing models capable of making multistep predictions, helping you understand and control complex systems.
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Use this if you need to build and evaluate deep learning or hybrid models for forecasting the behavior of dynamic systems like robots, chemical processes, or vehicles over multiple time steps.
Not ideal if you're looking for a simple, off-the-shelf prediction tool that doesn't require comfort with configuring models via JSON or managing command-line interfaces.
Stars
18
Forks
6
Language
Python
License
MIT
Category
Last pushed
Sep 25, 2025
Commits (30d)
0
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