Predicting Ionospheric Storm-time foF2 Using Support Vector Machine

摘要：

Using data from two ionosonde stations, Haikou and Chongqing, based on the knowledge gained from the variability of low latitude ionospheric storms, we have developed an empirical model using a new technique, Support Vector Machine, to predict the storm time F2 layer critical frequency, fof2. The model is driven by Dst, AE index and the historical data of fof2. Ionosonde data was sorted as a function of season, and the intensity of the storm, to obtain the corresponding dependencies. It indicated that the model described here can capture the low latitude storm time F2 layer variability at most times.

作者: Pan-Pan Ban Chun Chen Shu-Ji Sun Zheng-Wen Xu

作者单位: China Research Institute of Radiowave Propagation, Qingdao, China State Key Laboratory of Space Weat China Research Institute of Radiowave Propagation, Qingdao, China

会议类型: 国际会议

会议名称: 第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

会议地点: 广州

会议语种:英文

页码: 1-4

在线出版日期: 2010-11-29（万方平台首次上网日期，不代表论文的发表时间）