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相关论文: The Structure and Growth of Weighted Networks

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We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

统计力学 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

We propose a model for the growth of weighted networks that couples the establishment of new edges and vertices and the weights' dynamical evolution. The model is based on a simple weight-driven dynamics and generates networks exhibiting…

无序系统与神经网络 · 物理学 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

We propose a natural model of evolving weighted networks in which new links are not necessarily connected to new nodes. The model allows a newly added link to connect directly two nodes already present in the network. This is plausible in…

物理与社会 · 物理学 2011-08-18 Shinji Tanimoto

Many biological, ecological and economic systems are best described by weighted networks, as the nodes interact with each other with varying strength. However, most network models studied so far are binary, the link strength being either 0…

无序系统与神经网络 · 物理学 2009-11-07 S. H. Yook , H. Jeong , A. -L. Barabasi , Y. Tu

Many real systems possess accelerating statistics where the total number of edges grows faster than the network size. In this paper, we propose a simple weighted network model with accelerating growth. We derive analytical expressions for…

物理与社会 · 物理学 2008-11-20 Zhongzhi Zhang , Lujun Fang , Shuigeng Zhou , Jihong Guan

All crucial features of the recently observed real-world weighted networks are obtained in a model where the weight of a link is defined with a single non-linear parameter $\alpha$ as $w_{ij}=(s_is_j)^\alpha$, $s_i$ and $s_j$ are the…

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

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

Motivated by a recently introduced network growth mechanism that rely on the ranking of node prestige measures [S. Fortunato \emph{et al}., Phys. Rev. Lett. \textbf{96}, 218701 (2006)], a rank-based model for weighted network evolution is…

无序系统与神经网络 · 物理学 2015-06-25 Liang Tian , Da-Ning Shi , Chen-Ping Zhu

Inspired by scientific collaboration networks, especially our empirical analysis of the network of econophysicists, an evolutionary model for weighted networks is proposed. Both degree-driven and weight-driven models are considered.…

无序系统与神经网络 · 物理学 2007-05-23 Menghui Li , Jinshan Wu , Dahui Wang , Tao Zhou , Zengru Di , Ying Fan

Real-world networks process structured connections since they have non-trivial vertex degree correlation and clustering. Here we propose a toy model of structure formation in real-world weighted network. In our model, a network evolves by…

物理与社会 · 物理学 2015-06-26 C. C. Leung , H. F. Chau

For decades, complex networks, such as social networks, biological networks, chemical networks, technological networks, have been used to study the evolution and dynamics of different kinds of complex systems. These complex systems can be…

社会与信息网络 · 计算机科学 2020-12-16 Akrati Saxena

This paper presents an evolution model of weighted networks in which the structural growth and weight dynamics are driven by human behavior, i.e. passenger route choice behavior. Transportation networks grow due to people's increasing…

物理与社会 · 物理学 2007-09-27 Yihong Hu , Daoli Zhu , Nianqu Zhu

We study growing networks in which each link carries a certain weight (randomly assigned at birth and fixed thereafter). The weight of a node is defined as the sum of the weights of the links attached to the node, and the network grows via…

无序系统与神经网络 · 物理学 2009-11-10 T. Antal , P. L. Krapivsky

With the evolution of social networks, the network structure shows dynamic nature in which nodes and edges appear as well as disappear for various reasons. The role of a node in the network is presented as the number of interactions it has…

社会与信息网络 · 计算机科学 2018-03-02 Shailesh Kumar Jaiswal , Nabajyoti Medhi , Manjish Pal , Mridul Sahu , Prashant Sahu , Amal Dev Sarma

This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring…

物理与社会 · 物理学 2009-11-13 Giorgio Fagiolo , Javier Reyes , Stefano Schiavo

Many social, technological, biological, and economical systems are best described by weighted networks, whose properties and dynamics depend not only on their structures but also on the connection weights among their nodes. However, most…

无序系统与神经网络 · 物理学 2015-06-24 Chunguang Li , Guanrong Chen

Topology and weights are closely related in weighted complex networks and this is reflected in their modular structure. We present a simple network model where the weights are generated dynamically and they shape the developing topology. By…

物理与社会 · 物理学 2008-01-30 J. M. Kumpula , J. -P. Onnela , J. Saramaki , K. Kaski , J. Kertesz

Real world complex networks are scale free and possess meso-scale properties like core-periphery and community structure. We study evolution of the core over time in real world networks. This paper proposes evolving models for both…

社会与信息网络 · 计算机科学 2015-12-01 Akrati Saxena , S. R. S. Iyengar

Different weighted scale-free networks show weights-topology correlations indicated by the non linear scaling of the node strength with node connectivity. In this paper we show that networks with and without weight-topology correlations can…

无序系统与神经网络 · 物理学 2009-11-10 Ginestra Bianconi

We will introduce two evolving models that characterize weighted complex networks. Though the microscopic dynamics are different, these models are found to bear a similar mathematical framework, and hence exhibit some common behaviors, for…

无序系统与神经网络 · 物理学 2007-05-23 Bo Hu , Gang Yan , Wen-Xu Wang , Wen Chen
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