Improve short-term electricity consumption forecasting using a GA-based weighted fractional grey model
This study proposed a weighted fractional grey model (WFGM) based on a genetic algorithm for forecasting annual electricity consumption. WFGM has two parameters that can be used to adjust the order of the summation based on different data sequences and reflect the new information priority. The key i...
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主要な著者: | Shabri, Ani, Samsudin, Ruhaidah, Alromema, Waseem |
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フォーマット: | Book Section |
出版事項: |
Springer Science and Business Media Deutschland GmbH
2022
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オンライン・アクセス: | http://eprints.utm.my/id/eprint/99695/ http://dx.doi.org/10.1007/978-3-030-98741-1_6 |
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