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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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書誌詳細
主要な著者:	Sadaei, Hossein Javedani, Guimaraes, Frederico Gadelha, Cidiney Jose, Da Silva, Lee, Muhammad Hisyam @ Wee Yew, Tayyebe, Eslami
フォーマット:	論文
出版事項:	Elsevier Science BV 2017
主題:	Q Science
オンライン･アクセス:	http://eprints.utm.my/id/eprint/66169/ http://dx.doi.org/10.1016/j.ijar.2017.01.006
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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