Confidence and Quantitative Analysis of Wind Power Prediction Data Based on Fruit Fly Optimization Algorithm
Aiming at the problem of low accuracy and poor reliability of wind power prediction data,a confidence and quantita-tive analysis method of wind power prediction data based on fruit fly optimization algorithm is studied.The one-time exponen-tial smoothing method is used to smooth the historical wind speed data of wind power prediction,and the smoothed data are in-put into the LSSVM wind power prediction model,which sets the linear least square system as the loss function of support vec-tor machine.We select the fruit fly optimization algorithm to optimize the LSSVM wind power prediction model,set the root mean square error of wind power prediction as the fitness function of the fruit fly optimization algorithm,obtain the optimal pa-rameters of the LSSVM wind power prediction model,and quantitatively analyze the reliability of the wind power prediction da-ta.The experimental results show that the root mean square error of wind power predicted by this method is less than 0.3,which has high reliability of wind power prediction data.
fruit fly optimization algorithmwind powerforecast datareliabilityquantitative analysisLSSVM
万方数据
维普
