Wind speed prediction of extreme value type I distribution based on the Bayes method

Abstract:

In order to improve prediction accuracy of wind speed of extreme value type I distribution, the wind speed prediction model was proposed based on Jeffreys criterion and the Lindley approximation method of Bayesian theory. Monte Carl method was used to generate the pseudo wind speed samples, and the maximum likelihood parameter estimation method and Bayes statistical theory were used to estimate the wind prediction value of the extreme value type I distribution, then the prediction value was compared with the theoretical extreme value. The result indicates that the wind speed prediction model of extreme value type I distribution is more accurate than the maximum likelihood estimation. The accuracy increases with the increasing of pseudo wind speed sample numbers, but is not affected by the numbers of prior samples and prior variance for location parameter.