摘要
依据灰色系统理论和UT1–UTC的变化规律,以较少的观测样本建立了预报UT1–UTC的灰色系统模型,并将其与人工神经网络(artificial neural network,ANN)、最小二乘(least squares,LS)与自回归(autoregressive,AR)模型的组合(LS+AR)方法以及地球定向参数预报比较竞赛(Earth Orientation Parameters Prediction Comparison Campaign,EOP PCC)的预报结果进行对比.结果表明:灰色系统模型用于UT1–UTC预报是高效可行的,尤其是在1–10 d跨度的超短期预报中预报效果显著.
This work presents an application of the grey system model in the prediction of UT1–UTC. The short-term prediction of UT1–UTC is studied up to 30 days by means of the grey system model. The EOP（Earth orientation parameter） C04 time series with daily values from the International Earth Rotation and Reference Systems Service（IERS） serve as the data base. The results of the prediction are analyzed and compared with those obtained by the artificial neural network（ANN）, the combination of least squares（LS） and autoregressive（AR） model（LS＋AR）, and the Earth Orientation Parameters Prediction Comparison Campaign（EOP PCC）. The accuracies of the ultra short-term（1–10d） prediction are comparable to those obtained by the other prediction methods. The presented method is easy to use.
出处
《天文学报》
CSCD
北大核心
2016年第3期310-319,共10页
Acta Astronomica Sinica
基金
国家自然科学基金项目(11503031)资助
