Astronomy and Astrophysics – Astrophysics
Scientific paper
Jan 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012cha%26a..36...86z&link_type=abstract
Chinese Astronomy and Astrophysics, Volume 36, Issue 1, p. 86-96.
Astronomy and Astrophysics
Astrophysics
Scientific paper
Traditional methods for predicting the change in length of day (LOD change) are mainly based on some linear models, such as the least square model and autoregression model, etc. However, the LOD change comprises complicated non-linear factors and the prediction effect of the linear models is always not so ideal. Thus, a kind of non-linear neural network — general regression neural network (GRNN) model is tried to make the prediction of the LOD change and the result is compared with the predicted results obtained by taking advantage of the BP (back propagation) neural network model and other models. The comparison result shows that the application of the GRNN to the prediction of the LOD change is highly effective and feasible.
Wang Qi-Jie
Zhang Hao
Zhang Xiao-Hong
Zhu Jian-Jun
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