Periodic Pattern Discovery of Moving Objects Based on China Birding Data
Year: 2017
Type: article
Abstract: The trajectory data of moving objects contains a large amount of spatio-temporal information,and mining the periodic pattern hidden behind the spatio-temporal information is of great significance.In this paper,an algorithm for detecting the periodic pattern of the moving objects based on three stages is proposed.Through the study of the temporal and spatial characteristics of the trajectory points,it identifies and eliminates duplicate data.Density clustering algorithm is used to find the dense region of the locus and the periodic pattern of each moving object in the dense region,which solves the problem of the repetition of the trajectory data,the incontinuity of sampling data and the finding of the periodic pattern period of the moving objects.Experimental results based on 2003—2015 China birding record center,China Birding Report(CBR) and other public data show that this algoithm can process the trajectory data effectively and dig out the periodic pattern of the moving objects with regularity accurately.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3162173003