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In this study, the wind speed prediction model is created that gives a minimum error for different hidden layer neuron numbers and delay step numbers. Using the one-minute time series, the prediction of the next wind speed is performed with the NAR neural network model. The predicted values of wind speed obtained are compared with predicted values of wind speed obtained with filter methods. For different...
Wind energy is found to be a huge power resource ever since the time human civilization has evolved. Its importance has increased manifold as fossil fuel resources are depleting off quickly. However, the availability and variability of wind energy resource poses a high degree of hindrance to their integration into power grids leading to various power issues such as, deregulation of supply - load balance,...
Wind power presented a remarkable growth in the first decade of the 21st century, highly sustained by the economical and ecological benefits of this technology. Not only has it significantly contributed to reduce the dependence on fossil fuels in the production of electrical energy, wind power has also allowed to save great amounts of greenhouse gases emissions. This growth leads to an inevitable...
In this experiment, by using the method of artificial neural network and DPS DATA PROCESSING SYSTEM combined with the meteorological data of air temperature, relative air humidity, solar radiation, wind speed, soil water content and dew point temperature as the input variable, the author established the artificial neural network system to forecast the seedling water consumption of P.×euramericana...
Water consumption of plants is a key parameter for formulating irrigation system, and the precise prediction play a important role in improving the use efficiency of limited water resources. In this experiment, by using the method of artificial neural network and MATLAB DATA PROCESSING SYSTEM combined with the meteorological data of air temperature, relative air humidity, solar radiation, wind speed,...
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