计算机工程2017，Vol.43Issue(4)：1-7,7.DOI:10.3969/j.issn.1000-3428.2017.04.001
基于中国观鸟数据的移动对象周期模式发现
Periodic Pattern Discovery of Moving Objects Based on China Birding Data
摘要
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.关键词
移动对象/数据挖掘/数据预处理/周期模式/中国观鸟数据Key words
moving object/data mining/data preprocessing/periodic pattern/China birding data分类
信息技术与安全科学引用本文复制引用
陈东,邵增珍,魏争争,刘衍民..基于中国观鸟数据的移动对象周期模式发现[J].计算机工程,2017,43(4):1-7,7.基金项目
中国博士后科学基金(2016M592697) （2016M592697）
山东省科技发展计划项目(2014GGH201022) （2014GGH201022）
山东省经信委软科学研究课题(2015EI010). （2015EI010）
