Application of improved fuzzy clustering algorithm to analysis of trajectory

To optimize the present airspace structure using analysis of trajectory data,a trajectory data clustering analysis method was worked out. The basic FCM was improved on basis of GSAA. The features of trajectory were analyzed and abnormal values were handled. The proper values were extracted,which could represent the actual trajectory,by fuzzy subtractive clustering. They were clustered separately by basic FCM and improved FCM based on GSAA,and average tracks were made. At last,an example was calculated by two algorithms. The simulation results show that using improved FCM,the objective value is reduced by 15. 20%,comparing with that by FCM,and that with improved FCM,the clustering center would not to location where a large number of trajectory data points muster.