期刊文献+

一种基于周期模型的物联网实体实时预测方法

A Real-time Forecasting Method of Entities in Internet of Things Based on Cycle Models
下载PDF
导出
摘要 对物联网中实体的海量数据进行分析处理成为了物联网应用层发展的基础,很多应用场合需要对物联网实体状态进行预测。物联网中的实体状态具有强实时性和高动态性,通过判断物联网实体的周期模式采用合理的预测模型,对特定时间段建立时间窗口,预测出实体状态的概率值。该预测方法耗时短,能在2~4s给出预测结果,且准确度高,能与实际相符合,对物联网应用层的决策分析起到了很好的指示作用。 The analysis and processing of vast amounts of data of entities in the Internet of Things (IOT) has become the basis for the development of IOT application layer. Many applications need to predict the states of entities in IOT. States of entities in IOT are strong real-time and high dynamic. By judging cycle mode of entities in IOT and establishing the time window of a specific period of time, reasonable prediction model is used to predict the probability value of future state of entities. The prediction method is of short time-consuming and high accuracy. With this method, the prediction result can be given in 2 -4 s and it is in accordance with actual one. It plays a role of good indicator in the decision-making analysis of IOT ap- plication layer.
出处 《电讯技术》 北大核心 2013年第10期1347-1351,共5页 Telecommunication Engineering
关键词 物联网 应用层 实体状态 实时预测 周期模型 Internet of Things application layer entities state real-time forecasting cycle model
  • 相关文献

参考文献10

  • 1Chen L, Tseng M, Lian X. Development of foundation models for Internet of Things [ J ]. Frontiers of Computer Science in China, 2010, 4(3) : 376-385.
  • 2姚俊章,余永,葛运建.基于实时预测的传感器信号倍频算法[J].传感技术学报,2011,24(3):376-381. 被引量:1
  • 3刘志成,彭红星.传感器输出时间序列实时预测方法的比较研究[J].电子测量与仪器学报,2011,25(11):946-951. 被引量:5
  • 4裘江南,王延章,董磊磊,叶鑫.基于贝叶斯网络的突发事件预测模型[J].系统管理学报,2011,20(1):98-103. 被引量:37
  • 5Mietz R, Romer K. Exploiting correlations for efficient content- based sensor search [ C ]//Proceedings of 2011 IEEE International Conference on Sensors. Limerick: IEEE, 2011: 187-190.
  • 6Letchner J, Re C, Balazinska M, et al. Access methods for markovian streams [C]// Proceedings of IEEE 25th International Conference on Data Engineering. Shanghai: IEEE, 2009: 246-257.
  • 7Ostermaier B, Romer K, Mattern F, et al. A real-time search engine for the web of things [ C ]//Proceedings of 2010 IEEE International Conference on Intemet of Things ( IOT ). Tokyo : IEEE, 2010 : 1 - 8.
  • 8Elahi B M, Romer K, Ostermaier B, et al. Sensor ranking : A primitive for efficient content-based sensor search [C]//Proceedings of 2009 International Conference on Information Processing in Sensor Networks. San Francisco, CA : IEEE, 2009 : 217-228.
  • 9Reades J, Calabrese F, Sevtsuk A, et al. Cellular census: Explorations in urban data collection[J]. IEEE Pervasive Computing, 2007, 6 (3) : 30-38.
  • 10Elfeky M G, Aref W G, Elmagarmid A K. Using convoXution to mine obscure periodic patterns in one pass [ C ]//Proceedings of 9th International Conference on Extending Database Technology. Heraklion, Crete, Greece : IEEE ,2004 : 605-620.

二级参考文献31

共引文献40

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部