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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Format: | Article |
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Elsevier Inc.
2017
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Online Access: | http://eprints.utm.my/id/eprint/76329/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010953682&doi=10.1016%2fj.ijar.2017.01.006&partnerID=40&md5=8e4794ff52462862570959e801fd7c05 |
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Institution: | Universiti Teknologi Malaysia |