Genetic Algorithm Optimized CCEM for Complex Topology
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-01-11
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
To evaluate how much two different complex topologies are similar to each other in a quantitative way is an essential procedure in large-scale topology researches and still remains an NP problem.
Cross-correlation evaluation model (CCEM) together with Genetic Algorithm (GA) is introduced in this paper trying to solve this issue.
Experiments have proved that SLS (Signless Laplacian Spectra) is capable of identifying a topology structure and CCEM is capable of distinguishing the differences between corresponding topology SLS eigenvectors.
CCEM used in GA is recommended at last since a way of not finding the optimum solution in GA is a good way to reduce computing complexity.
American Psychological Association (APA)
Xu, Ye& Wang, Zhuo. 2012. Genetic Algorithm Optimized CCEM for Complex Topology. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1001556
Modern Language Association (MLA)
Xu, Ye& Wang, Zhuo. Genetic Algorithm Optimized CCEM for Complex Topology. Mathematical Problems in Engineering No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-1001556
American Medical Association (AMA)
Xu, Ye& Wang, Zhuo. Genetic Algorithm Optimized CCEM for Complex Topology. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1001556
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001556