Application of Genetic Algorithm Optimized Combination Model in Satellite Clock Error Prediction
In order to improve the accuracy of clock error prediction of navigation satellite,this paper introduces genetic algorithm(GA)and auto regression(AR)model on the basis of single BP(back propagation)neural network model,and constructs a new GA-BP-AR model.The combined model gives full play to the advantages of GA in network model parameter optimization and AR model in residual correction.Firstly,the original clock error is modeled and predicted by GA-BP model.Secondly,the prediction residual error is modeled and extrapolated by AR model;Finally,the final clock error prediction result is obtained by adding the GA-BP mod-el prediction value and the AR model residual prediction value.Two sets of satellite clock error data are used to test the effect of the combined model,and the experimental results are compared with the prediction results of a single model.The results show that the prediction accuracy of the combined forecasting model proposed in this paper is the highest,and the average accuracy is less than 0.3 ns,which verifies the superiority and applicability of the combined forecasting model proposed in this paper.
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