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我国智能交通系统(ITS)体系框架开发的关键技术 被引量:3

The Key Skill of Development and Research on Intelligent Transportation Systems(ITS) Architecture in China
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摘要 介绍了我国ITS体系框架开发的研究背景、概念、内容;明确提出了ITS体系框架的研究方法及开发思路,并对ITS体系框架的开发过程以图表形式作了详细说明,旨在全面了解我国ITS的开发研究;最后指出ITS技术的实施是解决当前交通问题的主要方式。 Development of ITS Architecture and Assistance Support System Research is the important project in China. The paper introduces the development background, the concept and the content, the research methods and the exploiture thoughtway of Intelligent Transportation Systems(ITS) Architecture in China; then the exploiture process of ITS architecture is interpreted in detail and continued ulteriorly in chart to understand ITS Architecture; lastly, the paper indicates that the establishing and actualizing ITS architecture is the main method of solving traffic problem at present in China.
出处 《交通科技与经济》 2008年第4期88-90,共3页 Technology & Economy in Areas of Communications
基金 国家"十五"科技攻关计划项目(2002BA404A26)
关键词 ITS 体系框架 开发 关键技术 Intelligent Transportation Systems(ITS) system develop key skill
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  • 1张可,齐彤岩,刘冬梅,王春燕,贺瑞华,刘浩.中国智能交通系统(ITS)体系框架研究进展[J].交通运输系统工程与信息,2005,5(5):6-11. 被引量:31
  • 2《中国智能运输系统体系框架》专题组.中国智能运输系统体系框架[M].北京:人民交通出版社,2002.
  • 3Miles,J.C,陈干主编;王笑京译.智能交通系统手册[M].北京:人民交通出版社,2007.
  • 4Sebastien G, Younes B. Selection of clusters number and features subset during a two-levels clustering task[C]//Proceeding of the 8th International Con- ference Artificial Intelligence and Soft Computing. Zakopane, Poland: [s. n. 7, 2006:28-33.
  • 5Macqueen J. Some methods for classification and analysis of multivariate observations[C]//Proceed- ing of 5th Berkeley Symposium on Mathematical Statistics and Probability. [S. 1.3 : University of Cal- ifornia Press, 1967:281-291.
  • 6Cabanes G, Bennani Y. A simultaneous two-level clustering algorithm for automatic model selection, machine learning and applications [C]//Sixth Inter- national Conference on Machine Learning and Appli- cations. Cincinnati, Ohio, USA.. IEEE Computer Society Press, 2007 : 316-321.
  • 7Meila M. Comparing clusterings--an information based distance [J]. Journal of Multivar Analysis, 2007,98(5), 873-895.
  • 8AI-Zoubi Mohrd Belal, Amiad H, Ammar H, et al. New efficient strategy to accelerate k-means cluster- ing algorithm[J]. American Journal of Applied Sci- ences, 2008,5(9) : 1247-1250.
  • 9Tan Zhenhua, Chang Guiran, Cheng Wei, et al. An improved peer-to-peer routing algorithm K-CSSP based on communication history clustered by k- means[C]//Ninth International Conference on Hy- brid Intelligent Systems. Shenyang, China: [s. n. ], 2009:381-385.
  • 10Zhang Zhenjie, Yang Yintung. Continuous k-means monitoring over moving objects[J]. Knowledge and Data Engineering, IEEE Transactions, 2008,20 (9) : 1025-1216.

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