DocumentCode
3431933
Title
Contracting community for computing maximum flow
Author
Zhang, YanPing ; Xu, Xiansheng ; Hua, Bo ; Zhao, Shu
Author_Institution
School of Computer Science and Technology, Anhui University, Hefei, 230039, China
fYear
2012
fDate
11-13 Aug. 2012
Firstpage
651
Lastpage
656
Abstract
In this paper, we propose a novel method named Contracting Community Approach (CCA) to get the maximum flow of flow network. Firstly, we contract communities in the original network. Then, we apply classic algorithms on the contracted network to approximately solve the maximum flow problem. Experimental results show that the efficiency of the proposed algorithm. For sparse networks, the size of network is reduced to 58.38% averagely and the correctness of maximum flow is over 95%. For middle dense networks, the size of network is reduced to 65.77% averagely. For dense networks, the size of network is reduced to 64.84% averagely. And the correctness of maximum flow even reach 100% both in many middle dense and dense cases in our experiments.
Keywords
Artificial neural networks; Educational institutions; Video recording; community; contracting; maximum flow; network;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing (GrC), 2012 IEEE International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4673-2310-9
Type
conf
DOI
10.1109/GrC.2012.6468649
Filename
6468649
Link To Document