A Nonlinear Ensemble Prediction Model Based on Genetic Algorithm for Calculation Wind of the Wind Assessment

Abstract

Following the thinking clue of the ensemble prediction in numerical weather prediction (NWP), a novel nonlinear artificial intelligence ensemble prediction (NAIEP) model for calculation wind speed of Mountain Darong in Guangxi has been developed based on the multiple neural networks with identical expected output created by using the genetic algorithm (GA) of evolutionary computation. The results show that the calculation accuracy by the nonlinear ensemble model of genetic - neural network for wind field is significantly higher than the traditional multiple linear regression model. Thus in practical application the long time sequence data of wind could be calculate according to the short time sequence data of the observation through the ANN nonlinear ensemble model, therefore this model is better practicability and popularize value for it provide the basis to research the exploitation wind resources.