Evolving Scale-Free Local Networks with Fitness and Tunable Clustering

Author

Ge, Min ; Chen, Xiaoping

Author_Institution

Sch. of Econ. & Manage., Jiangsu Teachers Univ. of Technol., Changzhou, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

Complex networks describe many real systems in nature and society more appropriately. Based on the recent complex networks research, an evolving scale-free local network model with fitness and tunable clustering is proposed in this paper. The result indicates: The analytical and numerical expressions of the model consistent with the numerical simulations well. Furthermore, the model explains the fitter-gets-richer phenomenon in local-world better, and helps us quantificationally comprehend many competitive systems´ evolution in nature and society.

Keywords

complex networks; pattern clustering; statistical distributions; competitive systems evolution; complex networks; fitness distribution; fitter-gets-richer phenomenon; scale-free local networks; tunable clustering; Appropriate technology; Clustering algorithms; Collaboration; Complex networks; Ecosystems; Educational technology; Equations; Numerical simulation; Social network services; Technology management;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5363699

Filename

5363699