title: Topology Universality and Dissimilarity in a Class of Scale-Free Networks.
abstract: We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extended models are evolved based on competition and inner anti-preferential deletion in growth and preferential attachment processes. By nonlinear and dynamic controlling on randomness and determinacy, three models can self-organize into scale-free networks, and diverse scaling exponents appear. Moreover, the model with more determinacy has more stringent parameter control than randomness, especially in the edge deletion. Our results suggest that the nature of the topology universality and dissimilarity in SF networks may be the subtle changes of randomness and determinacy.
authors: College of Information and Engineering, Taishan Medical University, Taian 271016, China.
authors: Lanhua
authors: L
authors: Zhang
authors: College of Information and Engineering, Taishan Medical University, Taian 271016, China.
authors: Juan
authors: J
authors: Chen
authors: College of Information and Engineering, Taishan Medical University, Taian 271016, China.
authors: Mei
authors: M
authors: Wang
authors: College of Information and Engineering, Taishan Medical University, Taian 271016, China.
authors: Yujuan
authors: Y
authors: Li
authors: Center for Cognition and Brain Disorders, Department of Psychology, Hangzhou Normal University, Hangzhou 310036, China.
authors: Shaowei
authors: S
authors: Xue
authors: Department of Psychological Sciences, Texas Tech University, TX 79409, United States of America.
authors: Yiyuan
authors: Y
authors: Tang
authors: Key Lab of Cerebral Microcirculation in Universities of Shandong, Taishan Medical University, Taian 271016, China.|Department of Neurology, Affiliated Hospital of Taishan Medical University, Taian 271000, China.
authors: Baoliang
authors: B
authors: Sun
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D003198:Computer Simulation; D008954:Models, Biological; D013269:Stochastic Processes