计算机技术与发展2018，Vol.28Issue(1)：41-44,50,5.DOI:10.3969/j.issn.1673-629X.2018.01.009
基于高斯分析的马尔可夫位置预测方法
A Location Prediction Method of Markov Based on Gaussian Analysis
摘要
Abstract
To solve the problem that the prediction results based on Markov model are rough due to the equivalent partition of time for deter-mining of transition time point,we propose a new location prediction method of Markov based on Gaussian analysis. First,it finds out the possible transition time points by using Gaussian mixed model fitting the transition probability of locations with continuous time,and establi-shes the Markov model by making these points to be the state transition points of the traditional Markov model. Finally it predicts the user' s location by calculating the probability of transition between states. The experiment on GeoLife dataset shows that the precision can be im-proved respectively by about 10％ and 12％ compared with Markov model and Gaussian mixture model.关键词
位置预测/基于位置的服务/轨迹数据/时间序列Key words
location prediction/location based service/trajectory data/time series分类
信息技术与安全科学引用本文复制引用
乔岩磊,杜永萍,赵东玥..基于高斯分析的马尔可夫位置预测方法[J].计算机技术与发展,2018,28(1):41-44,50,5.基金项目
国家科技支撑计划子课题(2013BAH21B02-01) （2013BAH21B02-01）
北京市自然科学基金资助项目(4153058) （4153058）
上海市智能信息处理重点实验室开放基金(IIPL-2014-004) （IIPL-2014-004）
