计算机科学 ›› 2014, Vol. 41 ›› Issue (7): 216-221.doi: 10.11896/j.issn.1002-137X.2014.07.045

• 软件与数据库技术 • 上一篇    下一篇

障碍空间中的移动对象位置预测

李实吉,秦小麟,施竣严   

  1. 南京航空航天大学计算机科学与技术学院 南京210016;南京航空航天大学计算机科学与技术学院 南京210016;南京航空航天大学计算机科学与技术学院 南京210016
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目(61373015),国家教育部高等学校博士学科点专项科研基金资助

Location Prediction of Moving Objects in Obstructed Space

LI Shi-ji,QIN Xiao-lin and SHI Jun-yan   

  • Online:2018-11-14 Published:2018-11-14

摘要: 移动对象的运动基本是在障碍空间里进行的。近几年,已有较多针对障碍空间中范围查询、近邻查询、聚类查询等的研究,但是目前尚没有对障碍空间中移动对象的位置预测进行研究。为此,研究了障碍空间中移动对象的位置预测;采用灰模型与线性模型相结合的办法,提出了一种基于R树的高效的剪枝算法;根据移动对象的运动规律性,提出了几条剪枝策略,从而大大减少了需要处理的障碍对象个数。最后,通过实验验证了算法的准确性和高效性。

关键词: 障碍空间,移动对象,预测,灰模型 中图法分类号TP311.131文献标识码A

Abstract: Most moving objects are typically influenced by obstacles.Recently,existing researches are mainly on range query,nearest neighbor query and spatial clustering query in obstructed space.However,there is no research on location prediction of moving object in obstructed space.This paper focused on location prediction of moving object in the pre-sence of obstacles.We proposed a efficient pruning method based on R-tree using gray model and line model.Conside-ring the trajectories of moving object are regular,we proposed several pruning strategies which can greatly reduce the number of searched obstacles.Finally,our experiment results demonstrate the accuracy and efficiency of the proposed approach.

Key words: Obstructed space,Moving object,Prediction,Gray model

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