The evolving Multivariable Gaussian (eMG) is a forecasting model classified as a rule-based evolving Fuzzy System (eFS) proposed by Lemos et al. [1].
The paper [2] has a complete review of the eFSs.
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eMG.py (https://github.com/kaikerochaalves/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/eMG.py) is the eMG model.
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MackeyGlass.py (https://github.com/kaikerochaalves/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/4b119c1706aae4d2934e4b7b5bc42b0b3abad13e/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/eMG/blob/e8b299491e78e182515da33af4f7043339b7c0e5/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.
[1] Lemos, A., Caminhas, W., & Gomide, F. (2010). Multivariable gaussian evolving fuzzy modeling system. IEEE Transactions on Fuzzy Systems, 19(1), 91-104.
[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.