Genetic Algorithm Optimized CCEM for Complex Topology

Joint Authors

Xu, Ye
Wang, Zhuo

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

Civil Engineering

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