| 广义回归神经网络在日长变化预报中的应用 |
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| 引用本文： | 张晓红,王琪洁,朱建军,张昊.广义回归神经网络在日长变化预报中的应用[J].天文学报,2011,52(4). |
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| 作者姓名： | 张晓红 王琪洁 朱建军 张昊 |
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| 作者单位： | 中南大学地球科学与信息物理学院 长沙 410083 |
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| 基金项目： | 国家自然科学基金委员会与中国科学院天文联合基金项目(10878026)资助 |
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| 摘 要： | 传统的日长变化预报多是基于线性模型,如最小二乘模型、自回归模型等,但是日长变化包含了复杂的非线性因素,线性模型预报的效果往往不甚理想.所以尝试使用一种非线性神经网络—广义回归神经网络(GRNN)模型进行日长变化预报,并将结果与使用BP (Back Propagation)神经网络模型和其它模型的预报结果进行比较.结果表明,GRNN用于日长变化预报是高效可行的.
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| 关 键 词： | 天体测量 时间 方法:其它诸多方面 |
An Application to the Prediction of LOD Change Based on General Regression Neural Network |
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| ZHANG Xiao-hong,WANG Qi-jie,ZHU Jian-jun,ZHANG Hao.An Application to the Prediction of LOD Change Based on General Regression Neural Network[J].Acta Astronomica Sinica,2011,52(4). |
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| Authors: | ZHANG Xiao-hong WANG Qi-jie ZHU Jian-jun ZHANG Hao |
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| Institution: | ZHANG Xiao-hong WANG Qi-jic ZHU Jian-jun ZHANG Hao (School of Geosciences and Info-Physics,Central South University,Changsha 410083) |
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| Abstract: | 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 a... |
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| Keywords: | astrornetry time methods:miscellaneous |
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