THE CLOCK DIFFERENC PREDICTION OF ATOMIC CLOCK BASED ON ELMAN NEURAL NETWORK

The clock difference prediction of the atomic clock is one of the parts in constructing the atomic time scale and controlling the time scale, so it is very important to explore high-precision clock difference prediction. As a feedback neural network that can dynamically remember, Elman neural network is very suitable for time series prediction. This paper proposes an algorithm of clock difference prediction based on Elman neural network, and uses the relevant data of the hydrogen clocks and cesium clocks from National Institute of Metrology (China) to conduct experiments in order to research the effectiveness of the algorithm. The experimental results show that the prediction algorithm which is proposed in this paper improves the prediction accuracy of clock difference compared with the prediction algorithm of linear regression, the prediction algorithm of support vector machine and the least square support vector machine.