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- W3157277934 abstract "Renewable energy production is increasing worldwide. In all the available renewable sources of energy wind energy has a major stake after hydro energy. However, intermittent nature of the wind speed is posing a constraint for the production of wind energy as stochastic wind power will de-stabilize the energy grid. The increase in demand of renewable sources of energy makes wind energy manufacturing a good investment in the upcoming future. To scheme an efficient regulation of the wind energy development, prediction of wind speed is quite beneficial. In this study, wind speed is predicted to mitigate and minimize the uncertainty in the production of wind power. So accordingly, four different machine learning techniques are applied and evaluated in this work for the Las Vegas region of U.S.A." @default.
- W3157277934 created "2021-05-10" @default.
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- W3157277934 date "2021-03-04" @default.
- W3157277934 modified "2023-09-23" @default.
- W3157277934 title "A Machine Learning Approach for Wind Speed Forecasting" @default.
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- W3157277934 doi "https://doi.org/10.1109/icacite51222.2021.9404563" @default.
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