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基于改进贝叶斯方法的轨迹预测算法研究
Alternative TitlePrediction of trajectory based on modified Bayesian inference
李万高; 赵雪梅; 孙德厂
Department数字工厂研究室
Source Publication计算机应用
ISSN1001-9081
2013
Volume33Issue:7Pages:1960-1963
Indexed ByCSCD
CSCD IDCSCD:4886855
Contribution Rank3
Funding Organization国家重大科技专项(2011ZX02507-006)
Keyword轨迹预测 马尔可夫模型 贝叶斯推理
Abstract针对传统轨迹预测方法在历史轨迹数目有限时,预测准确度较低的问题,提出一种改进的贝叶斯推理(MBI)方法,MBI构建了马尔可夫模型来量化相邻位置的相关性,并通过对历史轨迹进行分解来获得更准确的马尔可夫模型,最后得到改进的贝叶斯推理公式。实验结果表明,MBI方法比现有方法的预测速度快2到3倍,并且有较高的准确度和稳定性。MBI方法充分利用现有轨迹信息,不仅提高了查询效率,还保证了较高的预测精度。
Other AbstractThe existing algorithms for trajectory prediction have very low prediction accuracy when there are a limited number of available trajectories. To address this problem, the Modified Bayesian Inference (MBI) approach was proposed, which constructed the Markov model to quantify the correlation between adjacent locations. MBI decomposed historical trajectories into sub-trajectories to get more precise Markov model and the probability formula of Bayesian inference was obtained. The experimental results based on real datasets show that MBI approach is two to three times faster than the existing algorithm, and it has higher prediction accuracy and stability. MBI makes full use of the available trajectories and improves the efficiency and accuracy for the prediction of trajectory.
Language中文
Citation statistics
Cited Times:4[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/12473
Collection数字工厂研究室
Affiliation1.河南工程学院计算机学院
2.郑州升达经贸管理学院
3.中国科学院沈阳自动化研究所
Recommended Citation
GB/T 7714
李万高,赵雪梅,孙德厂. 基于改进贝叶斯方法的轨迹预测算法研究[J]. 计算机应用,2013,33(7):1960-1963.
APA 李万高,赵雪梅,&孙德厂.(2013).基于改进贝叶斯方法的轨迹预测算法研究.计算机应用,33(7),1960-1963.
MLA 李万高,et al."基于改进贝叶斯方法的轨迹预测算法研究".计算机应用 33.7(2013):1960-1963.
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