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- W2988149727 abstract "Abstract Nowadays, Operational power forecasts are associated with the one-value deterministic Numerical Weather Forecasting (NWF) simulation in the anticipated wind speed. This article introduced a novel predicting methodology called SSOFC-Apriori-WRP, which presents one-day-ahead wind power and speed forecasting. This methodology relies highly on a Weather Research and Prediction (WRP) simulation, a shark smell optimization (SSO), enhanced fuzzy clustering (EFC), and an Apriori association procedure. The wind speed prediction with the help of shaped WRP model was produced. Then by dividing wind speed predictions series into different parts, definite conditions were met and were introduced. Next the suggested methodology by the combination of SSO-optimized fuzzy clustering and Apriori algorithm withdraws the association rules, which are dominated among the anticipating errors in the divided waves and the shape features. The suggested methodology could be implemented to the other compared models and decrease the unreliability of the WRP simulation, if the association rules are used in the ultimate optimization process." @default.
- W2988149727 created "2019-11-22" @default.
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- W2988149727 date "2020-02-01" @default.
- W2988149727 modified "2023-10-03" @default.
- W2988149727 title "Day ahead powerful probabilistic wind power forecast using combined intelligent structure and fuzzy clustering algorithm" @default.
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- W2988149727 doi "https://doi.org/10.1016/j.energy.2019.116498" @default.
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