Short-term load forecasting method based on fuzzy time series, seasonality and long memory process
Seasonal Auto Regressive Fractionally Integrated Moving Average (SARFIMA) is a well-known model for forecasting of seasonal time series that follow a long memory process. However, to better boost the accuracy of forecasts inside such data for nonlinear problem, in this study, a combination of Fuzzy...
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| Pengarang-pengarang Utama: | , , , , |
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| Format: | Artikel |
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Elsevier Science BV
2017
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| Subjek-subjek: | |
| Capaian Atas Talian: | http://eprints.utm.my/66169/ http://eprints.utm.my/66169/ http://eprints.utm.my/66169/ |
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