Zheng-Meng/Reservoir-Computing-and-Hyperparameter-Optimization
Reservoir computing for short-and long-term prediction of chaotic systems, with tasks Lorenz and Mackey-Glass systems. Bayesian optimization (hyperparameter optimization algorithm) is used to tune the hyperparameters and improve the performance.
If you're trying to predict complex time-series data from chaotic systems, this project helps you achieve accurate short- and long-term forecasts. It takes your historical data (like sensor readings or financial time series) and produces future predictions. This is ideal for scientists, engineers, or researchers working with dynamic, non-linear systems.
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Use this if you need to accurately predict the future behavior of chaotic systems, like atmospheric convection or biological population dynamics, and want to optimize the prediction model's performance.
Not ideal if your data is not a time series from a chaotic system or if you are looking for a general-purpose machine learning model without a focus on recurrent networks.
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2
Language
MATLAB
License
MIT
Category
Last pushed
Jul 19, 2025
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