Genetic Algorithm Optimized CCEM for Complex Topology

Ye Xu and Zhuo Wang

Mathematical Problems in Engineering, 2012, vol. 2012, 1-14

Abstract:

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.

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2012/383248.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2012/383248.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:383248

DOI: 10.1155/2012/383248

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().