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相关论文: The urban economy as a scale-free network

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The presented model provides an explanation to several empirically observed phenomena in spatial economics. By representing the system as a complex network of fixed-size land areas connected by trade between harbored activities, city size…

统计力学 · 物理学 2007-05-23 Claes Andersson , Alexander Hellervik , Kristian Lindgren

We present a novel type of weighted scale-free network model, in which the weight grows independently of the attachment of new nodes. The evolution of this network is thus determined not only by the preferential attachment of new nodes to…

无序系统与神经网络 · 物理学 2007-07-24 Takuma Tanaka , Toshio Aoyagi

Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information…

无序系统与神经网络 · 物理学 2016-08-31 Albert-Laszlo Barabasi , Reka Albert , Hawoong Jeong

The increased availability of data on real networks has favoured an explosion of activity in the elaboration of models able to reproduce both qualitatively and quantitatively the measured properties. What has been less explored is the…

无序系统与神经网络 · 物理学 2007-05-23 Thomas Petermann , Paolo De Los Rios

We analyze about two hundred naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned…

We propose a geometric growth model for weighted scale-free networks, which is controlled by two tunable parameters. We derive exactly the main characteristics of the networks, which are partially determined by the parameters. Analytical…

物理与社会 · 物理学 2011-11-09 Zhongzhi Zhang , Shuigeng Zhou , Lichao Chen , Jihong Guan , Lujun Fang , Yichao Zhang

Scale-free power law structure describes complex networks derived from a wide range of real world processes. The extensive literature focuses almost exclusively on networks with power law exponent strictly larger than 2, which can be…

社会与信息网络 · 计算机科学 2015-09-29 Harry Crane , Walter Dempsey

What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is…

统计力学 · 物理学 2007-05-23 Gang Yan , Tao Zhou , Ying-Di Jin , Zhong-Qian Fu

Modeling human dynamics responsible for the formation and evolution of the so-called social networks - structures comprised of individuals or organizations and indicating connectivities existing in a community - is a topic recently…

计算机与社会 · 计算机科学 2007-05-23 Victor V. Kryssanov , Frank J. Rinaldo , Evgeny L. Kuleshov , Hitoshi Ogawa

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

统计力学 · 物理学 2007-05-23 M. Baiesi , S. S. Manna

Network growth is currently explained through mechanisms that rely on node prestige measures, such as degree or fitness. In many real networks those who create and connect nodes do not know the prestige values of existing nodes, but only…

无序系统与神经网络 · 物理学 2007-05-23 Santo Fortunato , Alessandro Flammini , Filippo Menczer

Scale-free networks constitute a fast-developing field that has already provided us with important tools to understand natural and social phenomena. From biological systems to environmental modifications, from quantum fields to high energy…

综合物理 · 物理学 2021-06-17 Airton Deppman , Evandro Oliveira Andrade Segundo

We show how scale-free degree distributions can emerge naturally from growing networks by using random walks for selecting vertices for attachment. This result holds for several variants of the walk algorithm and for a wide range of…

统计力学 · 物理学 2007-05-23 T. S. Evans , J. P. Saramaki

Many real-world networks display a natural bipartite structure. Investigating it based on the original structure is helpful to get deep understanding about the networks. In this paper, some real-world bipartite networks are collected and…

物理与社会 · 物理学 2008-04-25 Peng Zhang , Menghui Li , J. F. F. Mendes , Zengru Di , Ying Fan

Scale-free and non-computable characteristics of natural networks are found to result from the least-time dispersal of energy. To consider a network as a thermodynamic system is motivated since ultimately everything that exists can be…

综合物理 · 物理学 2011-06-22 Tuomo Hartonen , Arto Annila

We introduce a new mechanism of connectivity evolution in networks to account for the emergence of scale-free behavior. The mechanism works on a fixed set of nodes and promotes growth from a minimally connected initial topology by the…

统计力学 · 物理学 2007-05-23 Valmir C. Barbosa , Raul Donangelo , Sergio R. Souza

We study a modified version of a model previously proposed by Jackson and Wolinsky to account for communicating information and allocating goods in socioeconomic networks. In the model, the utility function of each node is given by a…

物理与社会 · 物理学 2009-11-13 Rui Carvalho , Giulia Iori

Many complex systems--from social and communication networks to biological networks and the Internet--are thought to exhibit scale-free structure. However, prevailing explanations rely on the constant addition of new nodes, an assumption…

适应与自组织系统 · 物理学 2022-11-10 Christopher W. Lynn , Caroline M. Holmes , Stephanie E. Palmer

Co-evolution exhibited by a network system, involving the intricate interplay between the dynamics of the network itself and the subsystems connected by it, is a key concept for understanding the self-organized, flexible nature of…

物理与社会 · 物理学 2012-11-14 Takaaki Aoki , Toshio Aoyagi

A spatial scale-free network is introduced and studied whose motivation has been originated in the growing Internet as well as the Airport networks. We argue that in these real-world networks a new node necessarily selects one of its…

统计力学 · 物理学 2009-11-11 G. Mukherjee , S. S. Manna
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