Abstract Considering the shortcomings of the traditional GM(1,1)+AR combination model, we propose a cyclic clock bias prediction model, which can update the modeling sequence in time and enhance the correlation between the data. The order of AR model is adjusted in real time according to different forecast times. Considering the influence of the original clock bias modeling sequence length on prediction accuracy, the clock bias sequences of 2 h, 6 h, 12 h and 24 h are used to build the model respectively. The results show that the prediction accuracy of the improved model is superior to the traditional method, and the prediction results are more stable. Using clock bias series with different lengths to build the model will have a certain impact on the prediction results, among which the quadratic polynomial model is relatively more affected by the length of the original series, and the improved model is relatively less affected.
GUO Zhongchen,SUN Peng,LI Zhichun. Research on the Improved Algorithm of Clock Bias Short-Term Prediction Based on GM(1,1)+AR Model[J]. jgg, 2020, 40(9): 907-912.
GUO Zhongchen,SUN Peng,LI Zhichun. Research on the Improved Algorithm of Clock Bias Short-Term Prediction Based on GM(1,1)+AR Model[J]. jgg, 2020, 40(9): 907-912.