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- W2017508730 abstract "An algorithm is proposed that automatically generates the fuzzy rules from time series data and can subsequently be used for forecasting of the same time series. The effectiveness of the algorithm, measured by the performance indices such as the sum squared error (SSE), root mean squared error (RMSE/MSE) and the mean absolute error (MAE), is demonstrated on forecasting of chaotic time series, as well as on forecasting of homogeneous non-stationary time series with and without seasonality and trend components." @default.
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- W2017508730 date "1999-01-01" @default.
- W2017508730 modified "2023-09-26" @default.
- W2017508730 title "Fuzzy logic based automatic rule generation and forecasting of time series" @default.
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- W2017508730 doi "https://doi.org/10.1109/fuzzy.1999.793266" @default.
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