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• W2767914405 abstract "In this study, artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) were applied to estimate the wind turbine power output of a horizontal axis wind turbine. Hub-height wind speed, atmospheric air temperature and rotational speed values obtained from an operating wind power plant (WPP) were employed as input data in the model. According to the derived results, the mean absolute percentage error (MAPE) and correlation coefficient (R) values for the ANN model were determined as 4.41% and 0.9850, respectively, whereas the corresponding values for the ANFIS model were found as 2.19% and 0.9971, respectively. The obtained results showed that ANN and ANFIS models can be used to predict wind turbine power output in a simple, reliable and accurate way." @default.
• W2767914405 created "2017-11-17" @default.
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• W2767914405 date "2017-08-01" @default.
• W2767914405 modified "2023-10-03" @default.
• W2767914405 title "Modelling of wind turbine power output by using ANNs and ANFIS techniques" @default.
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• W2767914405 doi "https://doi.org/10.1109/intech.2017.8102425" @default.
• W2767914405 hasPublicationYear "2017" @default.
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