Improved K-Means Clustering for Target Activity Regular Pattern Extraction with Big Data Mining

摘要

The traditional target activity regular pattern extraction methods replay previous target tracks, activities of the specified target are manually analyzed by checking all the tracks on map. This paper adopts big data mining technology to solve the problem of automatically extracting target classic tracks and converts the original pure manual map analysis into system automatic track extraction. This method greatly reduces the operation intervention of classic track extraction, which can reduce the 3-4 manual days to 3-4 h.