摘要
高准确度的时间尺度是由原子钟建立并保持的,它需要连续测量,但由于设备延迟或外界环境突变等因素,会造成数据丢失,对原子钟的测量结果分析将产生较大的影响,利用二次多项式模型能够对丢失数据进行修正,但对连续多个丢失数据点的修正精度并不理想。利用灰色模型和两种组合模型对丢失数据进行预报和修正,对四种模型的预报精度进行了比较。实验结果表明,采用两种组合模型的预报精度高于二次多项式模型和灰色模型,验证了组合模型的可行性和有效性。
High accuracy of time scale is established and maintained by atomic clocks. During the continuous measurement, the measurement data may get lost due to the delay of the equipment or the sudden change in the outside environment. The quadratic polynomial model can be used to predict and correct the lost data, but it’s not good when dealing with continuous lost data. This paper uses grey model and another two combined models to predict and correct the lost data, and also com-pares the four models’prediction accuracy. It turns out that using the two combined models has higher accuracy over the quadratic polynomial model and grey model, so the combined models are effective and feasible.
出处
《计算机工程与应用》
CSCD
2014年第9期254-257,共4页
Computer Engineering and Applications
关键词
二次多项式模型
灰色模型
原子钟
数据丢失
残差
组合模型
quadratic polynomial model
grey model
atomic clock
lost data
residual errors
combined model
