Forecasting Model of Geomagnetic Variation Field Based onModified Ensemble Empirical Mode Decomposition-SampleEntropy-Least Square Support Vector Machine

Objective Modeling and forecasting of the geomagnetic variation field is the important research topic ofgeomagnetic navigation and space environment monitoring.According to the chaotic feature of geo-magnetic variation time series,a combined forecasting model based on modified ensemble empiricalmode decomposition(MEEMD)-sample entropy(SampEn)-least square support vector machine(LSS-VM)is proposed.Firstly,the geomagnetic variation time series is decomposed into a series of geo-magnetic variation subsequences with obvious differences in complex degree using MEEMD-SampEn.Then,the forecasting model of each subsequence is created with LSSVM using the optimal model pa-rameters.Finally,the simulation is performed by using the real data collected from the geomagneticobservatory.The results show that the forecasting value of the MEEMD-SampEn-LSSVM model canclosely keep up with the trend of geomagnetic variation field,and obviously better than the other twomodels.The mean absolute error of the model forecasting three hours is 1.63nT when Kplessthan 3.