An Application to the Prediction of LOD Change Based on General Regression Neural Network

Details An Application to the Prediction of LOD Change Based on General Regression Neural Network An Application to the Prediction of LOD Change Based on General Regression Neural Network

Jul 2011

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011acasn..52..322z&link_type=abstract

Acta Astronomica Sinica, vol. 52, no. 4, p. 322-331

Computer Science

Performance

Astrometry, Time, Methods: Miscellaneous

Scientific paper

Traditional prediction of the LOD (length of day) change was based on linear models, such as the least square model and the autoregressive technique, etc. Due to the complex non-linear features of the LOD variation, the performances of the linear model predictors are not fully satisfactory. This paper applies a non-linear neural network - general regression neural network (GRNN) model to forecast the LOD change, and the results are analyzed and compared with those obtained with the back propagation neural network and other models. The comparison shows that the performance of the GRNN model in the prediction of the LOD change is efficient and feasible.

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