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网络连通度算法的性能分析与比较
引用本文:孙小军,王志强,刘三阳.网络连通度算法的性能分析与比较[J].福州大学学报(自然科学版),2012,40(3):299-303.
作者姓名:孙小军  王志强  刘三阳
作者单位:宝鸡文理学院数学系;总装备部驻天水地区军事代表室;西安电子科技大学理学院
基金项目:陕西省教育厅科研资助项目(11JK0509);宝鸡文理学院重点科研项目(ZK11131)
摘    要:从四个方面分析和比较了两种求解网络连通度问题的算法性能.结果表明,在相同的计算环境下,两种算法的计算结果相同,但与基于最大流方法的算法相比,基于影响度向量的算法由于每次迭代只需要计算和存储点影响度向量和网络影响度向量,具有更高的计算效率,需要更小的存储空间,并且易于计算机实现.

关 键 词:网络连通度  最大流方法  影响度向量  算法

Performance analysis and comparison of algorithms for measures of network connectivity
SUN Xiao-jun,WANG Zhi-qiang,LIU San-yang.Performance analysis and comparison of algorithms for measures of network connectivity[J].Journal of Fuzhou University(Natural Science Edition),2012,40(3):299-303.
Authors:SUN Xiao-jun  WANG Zhi-qiang  LIU San-yang
Institution:1.Department of Mathematics,Baoji University of Art and Sciences,Baoji,Shanxi 721006,China; 2.General Armament Department Military Representative Office in Tianshui Region,Baoji,Shanxi 721006,China; 3.School of Science,Xidian University,Xi’an,Shanxi 710071,China)
Abstract:Two algorithm’s performances on the network connection problem are analyzed and compared in this paper from four aspects.It shows that the two analyzed algorithms present the same result in the same computing environment.However,compared with the algorithm based on the maximum flow method,the algorithm which is based on influence vector is of better computation efficiency and smaller storage room with the reason that it only needs to compute and store the influence vector of point and network in single iteration.Besides,it is easy to program and calculate.
Keywords:network connectivity  maximum flow method  influence vector  algorithm
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