Spatiotemporal Analysis of Travel Modes Based on an Adaptive Grid Density Algorithm
A trajectory data preprocessing method and a region mining algorithm based on adaptive grid density big data are proposed to address the drawbacks of noise in taxi GPS raw trajectory data,high processing costs for big data,difficulty in parame-ter selection,and susceptibility to clustering effects in traditional density algorithms.The research results indicate that the adaptive grid density algorithm can effectively avoid the parameter adjustment process,has strong sample space adaptability,and high clus-tering quality.Compared with conventional density clustering algorithms,it has lower computational complexity and higher computa-tional efficiency.The spatiotemporal characteristics of Chongqing residents'travel patterns provided are in line with reality and have practical value.
国家科技期刊平台
NSTL
万方数据
