Collective adaptation evolution of weighted complex networks: on syncronizability dependence
| dc.authorid | https://orcid.org/0000-0001-8766-6742 | en_US |
| dc.contributor.author | Jing, Yuanwei | |
| dc.contributor.author | Wang, Dan | |
| dc.contributor.author | Dimirovski, Georgi M. | |
| dc.date.accessioned | 2019-12-09T05:48:09Z | |
| dc.date.available | 2019-12-09T05:48:09Z | |
| dc.date.issued | 2017 | en_US |
| dc.department | Doğuş Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | en_US |
| dc.description | Dimirovski, Georgi M. (Dogus Author) -- Conference full title: 13th IEEE International Conference on Control and Automation, ICCA 2017; Ohrid; Macedonia; 3 July 2017 through 6 July 2017. | en_US |
| dc.description.abstract | An innovated evolving network representation model to characterize weighted, complex, scale-free networks is proposed. A new node or a community is added to network in the process of evolution while emergences of new links occur according to the 'Triad Formation' possessing symmetry and the random selection mechanism. A weighted scale-free network with high-value clustering coefficient can be obtained by adjusting two parameters only. The evolution of degree, strength, weights exhibit the power-law distributions. Highly correlated with the degree, the average strength displays scale-free property. The average clustering coefficient is found to exhibit well power-law decay as a function of the node degree. Triad Formation and Community Structure in weighted scale-free evolving networks, as building mechanisms, can distinctly enhance the clustering coefficient of networks. Both type I and type II networks are found their synchronizability to decrease as the average clustering coefficient increases in weighted scale-free networks of communities. | en_US |
| dc.identifier.citation | Jing, Y., Wang, D., & Dimirovski, G. M. (2017). Collective adaptation evolution of weighted complex networks: on syncronizability dependence. In 13th IEEE International Conference on Control and Automation (pp. 88-93). Ohrid: IEEE. http://dx.doi.org/10.1109/ICCA.2017.8003040 | en_US |
| dc.identifier.doi | 10.1109/ICCA.2017.8003040 | |
| dc.identifier.endpage | 93 | en_US |
| dc.identifier.isbn | 9781538626795 | |
| dc.identifier.isbn | 9781538626788 | |
| dc.identifier.isbn | 9781538626801 | |
| dc.identifier.issn | 1948-3449 | |
| dc.identifier.issn | 1948-3457 | |
| dc.identifier.other | 17084127 (INSPEC) | |
| dc.identifier.scopus | 2-s2.0-85029901857 | en_US |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.startpage | 88 | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1109/ICCA.2017.8003040 | |
| dc.identifier.uri | https://hdl.handle.net/11376/3463 | |
| dc.identifier.wos | WOS:000427123500016 | en_US |
| dc.identifier.wosquality | N/A | en_US |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.institutionauthor | Dimirovski, Georgi M. | |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.ispartof | 13th IEEE International Conference on Control & Automation | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Clustering Coefficient | en_US |
| dc.subject | Collective Adaptation | en_US |
| dc.subject | Community Structures | en_US |
| dc.subject | Complex Networks | en_US |
| dc.title | Collective adaptation evolution of weighted complex networks: on syncronizability dependence | en_US |
| dc.type | Conference Object | en_US |












