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利用海口、广州、满洲里、兰州、北京和乌鲁木齐2003年的电离层电子浓度总含量(TEC)数据讨论了电离层TEC的混沌特性及其预报.采用自相关法确定延迟时间τ,综合Cao算法和饱和关联维法(G-P算法)的结果确定嵌入维数m.结果表明:当τ=2,m=6时,可对电离层TEC进行相空间重构,且重构后轨迹的李雅普诺夫指数均为正,应证电离层TEC具有混沌特性.在此基础上采用相空间重构和支持向量机相结合的方法对以上6个站点2003年的电离层TEC数据进行预报,将得到的结果同常用的加权一阶局域法与自适应预报进行比较,发现其预报效果最佳,预报的平均相对精度相对于加权局域法均提高10%以上,最大提升了31.1%;预报的相对精度大于95%的占50%以上,而自适应预报只有25%左右.
The chaotic characteristics of ionospheric TEC and its prediction are discussed based on the total ionospheric electron concentration (TEC) data of Haikou, Guangzhou, Manzhouli, Lanzhou, Beijing and Urumqi in 2003. The autocorrelation method is used to determine the delay time τ, The results of the saturated correlation dimension method (GP algorithm) confirm the embedding dimension m. The results show that when τ = 2 and m = 6, phase space reconstruction can be performed on the ionospheric TEC. The Lyapunov exponents All of them are positive and the ionospheric TEC should be characterized by chaos.On the basis of above, the ionospheric TEC data of the above six sites are predicted by the combination of phase space reconstruction and support vector machine, and the results obtained are the same as Compared with the adaptive prediction, the weighted first-order local method generally found the best prediction result. The average relative accuracy of the prediction is increased by more than 10% and the maximum relative increase by 31.1%. The relative accuracy of the prediction is greater than 95% account for more than 50%, while adaptive forecast is only about 25%.