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《Journal of Geodesy and Geodynamics》 2014-06
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Lu Chenlong;Kuang Cuilin;Zhang Jinsheng;Chen Yulin;School of Geosciences and Info-Physics,Central South University;NASMG Key Laboratory of Land Environment and Disaster Monitoring;  
Based on the nonlinear and non-stationary characteristics of total electric contents time series,the combination of SSA method and ARMA model was proposed to predict TEC. In the combination,ARMA model is used to predict the data which had been decomposed and filtered by SSA method,and the predicted value of each component is overlaid. The results calculated by the combination for 2010 TEC data show that the mean relative precision of TEC prediction for 5 days is 92% by the combination,and the accuracy is improved of 4%,comparing with individual ARMA method.
【Fund】: 国土环境与灾害监测国家测绘地理信息局重点实验室开放基金项目(LEDM2013B02);; 湖南省国土资源厅科技项目(2012-41)
【CateGory Index】: P352
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