期刊文献+

熵权法对融合网络服务质量效率保障研究 被引量:3

Research on Entropy Coefficient to Guarantee Efficiency of QoS in Conversion Network
下载PDF
导出
摘要 融合网络业务和技术的差异直接导致服务质量和带宽的利用率矛盾加大,服务质量算法的权重确定是决定带宽分配有效性的重要依据,融合网络对权重的确定过程非常复杂,基于熵的概念对其权重给予确定是一种新的方法,论文通过分析和模拟确定了它的可行性和有效性。 Weighted coefficient is an important complication to determine availability of bandwidth allocation in fair algorithm and weights coefficient is very complexity,Tbe antinomy is enlarging between QoS and bandwidth efficiency because there are many differences between application and technology of the conversion network.This paper proposes a new idea to determine weights coefficient based on entropy and proves it is provided with feasibility and availability。
作者 陈雷 王延章
出处 《计算机工程与应用》 CSCD 北大核心 2005年第23期1-3,共3页 Computer Engineering and Applications
基金 国家自然科学基金资助项目(编号:60074038 60003006)
关键词 熵权 融合网络 QOS 带宽利用率 Entropy coefficient,conversion network,QoS,bandwidth efficiency
  • 相关文献

参考文献7

二级参考文献8

共引文献346

同被引文献22

  • 1陈孝新.熵权法在股票市场的应用[J].商业研究,2004(16):139-140. 被引量:9
  • 2杨世兴.煤矿监测监控系统的现状与发展[J].安防科技(安全经理人),2004(5):39-41. 被引量:32
  • 3MUATA K, BRYSO O. Towards supporting expert evaluation of clustering results using a data mining process model[ J]. Information Sciences, 2010, 180(3) : 414 -431.
  • 4CAO F Y, LIANG J Y, JIANG G. An initialization method for the K- means algorithm using neighborhood model [ J]. Computers and Mathematics with Applications, 2009, 58(3) :474 -483.
  • 5ALIK K R. An efficient K-means clustering algorithm[ J]. Pattern Recognition Letters, 2008, 29(9) : 1385 - 1391.
  • 6REDMOND S J, HENEGHAN C. A method for initialising the K-means clustering algorithm using KD-trees[ J]. Pattern Recognition Letters, 2007, 28(8) : 965 -973.
  • 7LAI J Z C, HUANG T J, LIAW Y C. A fast K-means clustering algorithm using cluster center displacement[ J]. Pattern Recognition, 2009,42(11): 2551 -2556.
  • 8HAN J W, KAMBER M. Data mining concepts and techniques [ M]. 2nd ed. San Francisco: Morgan Kaufmann Publishers, 2006: 383 -461.
  • 9UCI Machine Learning Repository [ DB/OL]. [ 2010 - 12 - 20]. http://archive, ics. uci. edu/ml/.
  • 10AHMAD A, DEY L. A k-mean clustering algorithm for mixed numeric and categorical data[ J]. Data & Knowledge Engineering, 2007, 63 (2) : 503 - 527.

引证文献3

二级引证文献47

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