空间科学学报2012，Vol.32Issue(2)：204-208,5.
利用人工神经网络提前1h预报电离层TEC
Forecasting of Ionospheric TEC One Hour in Advance by Artificial Neural Network
摘要
Abstract
A handy method of forecasting the ionospheric TEC one hour ahead by Artificial Neural Network （ANN） is presented in this paper. Considering of the practical application, the observations of TEC are used as inputs without any other data. The input parameters are the present observation of TEC, the first difference and relative difference of TEC, and the local time. The output is the TEC one hour ahead. Ionospheric TEC data evaluated from GPS measurements at Xiamen receiving station is used to checkout the forecasting method. The relative error is 9.3744%, and the cross correlation coefficient between the observed and forecast TEC values is 0.96678. The accuracy rate of relative error less than 15% is 79.59%, during the geomagnetic storms, but 98.81% for the quiet or moderate geomagnetic conditions. These conclusions suggest that the value of forecasting is very the geomagnetic level. It is shown that the Artificial Neural Network is promising in forecasting of ionospheric TEC one hour ahead.关键词
电离层电子总含量/电离层预报/人工神经网络Key words
Ionospheric TEC/Ionospheric forecast/Artificial Neural Network (ANN)分类
天文与地球科学引用本文复制引用
翁利斌,方涵先,缪子青,杨升高..利用人工神经网络提前1h预报电离层TEC[J].空间科学学报,2012,32(2):204-208,5.基金项目
解放军理工大学气象学院预研基金资助项目 （）
