%0 Journal Article
%A GUO Wei-qiang
%A ZHAO Zhuo-feng
%A ZHANG Kuan
%T Travel Recognition Method for Fixed-Point Trajectory Data
%D 
%R 10.13190/j.jbupt.2019-216
%J Journal of Beijing University of Posts and Telecommunications
%P 39-47
%V 43
%N 4
%X To satisfy the requirements of long-periodic fixed-point trajectory travel recognition,a dynamic threshold travel recognition method for fixed point trajectory data is proposed. At first,use hierarchical clustering to determine the spatial-temporal multiple granularity parameters which relate to the threshold. Then count historical records according to parameters to calculate the threshold corresponding to each parameter. Last,execute trajectory segmentation process with spatial-temporal threshold to get the precise travel recognition result. Experiment based on fixed-point trajectory data from real world city shows that using spatial-temporal dynamic threshold method to recognize travel in fixed point trajectory data is superior to the traditional stable and single threshold method on accuracy and coverage.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2019-216