The evolving Takagi-Sugeno (eTS) is a forecasting model classified as a rule-based evolving Fuzzy System (eFS) proposed by Angelov and Filev [1].
The paper [2] has a complete review of the eFSs.
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eTS.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/eTS.py) is the eTS model.
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MackeyGlass.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/MackeyGlass.py) is the script to prepare the Mackey-Glass time series, perform simulations, compute the results and plot the graphics.
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Nonlinear.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/Nonlinear.py) is the script to prepare the nonlinear dynamic system identification time series, perform simulations, compute the results and plot the graphics.
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LorenzAttractor.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/LorenzAttractor.py) is the script to prepare the Lorenz Attractor time series, perform simulations, compute the results and plot the graphics.
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NASDAQ.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/NASDAQ.py) is the script to prepare the NASDAQ time series, perform simulations, compute the results and plot the graphics.
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SP500.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/SP500.py) is the script to prepare the S7P 500 time series, perform simulations, compute the results and plot the graphics.
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TAIEX.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/TAIEX.py) is the script to prepare the TAIEX time series, perform simulations, compute the results and plot the graphics.
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PowerTransformerDay1.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/PowerTransformerDay1.py) is the script to prepare the dataset of the power transformers on day 1, perform simulations, compute the results and plot the graphics.
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PowerTransformerDay2.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/PowerTransformerDay2.py) is the script to prepare the dataset of the power transformers on day 2, perform simulations, compute the results and plot the graphics.
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PowerTransformerDay3.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/PowerTransformerDay3.py) is the script to prepare the dataset of the power transformers on day 3, perform simulations, compute the results and plot the graphics.
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PowerTransformerAllDays.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/3f0f3762e0990496820617da608a7e77767e8966/PowerTransformerAllDays.py) is the script to prepare the dataset of the power transformers on day 1 to train the model, and days 2 and 3 to perform simulations, compute the results and plot the graphics.
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GridSearch_AllDatasets.py (https://github.com/kaikerochaalves/eTS-evolving-Takagi-Sugeno/blob/b634609bb2af9d70a52026d30cac43e5a868ab30/GridSearch_AllDatasets.py) is the script performing a grid search for the hyperparameters for all datasets.
[1] P. Angelov, D. Filev, On-line design of takagi-sugeno models, in: International Fuzzy Systems Association World Congress, Springer, 2003, pp. 576–584, http://dx.doi.org/10.1007/3-540-44967-1_69.
[2] K.S.T.R. Alves, E. P. Aguiar, A novel rule-based evolving Fuzzy System applied to the thermal modeling of power transformers. Appl. Soft Comput. 112 (2021) 107764-107764, https://doi.org/10.1016/j.asoc.2021.107764.