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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Main Authors: | , , , , |
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Format: | Article |
Published: |
Elsevier Science BV
2017
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/66169/ http://dx.doi.org/10.1016/j.ijar.2017.01.006 |
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Institution: | Universiti Teknologi Malaysia |
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