复杂网络的链路预测

在基于节点的攻击引发的级联故障中识别复杂网络中的易受攻击的节点

Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems, metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among the others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging pre- sentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and social sciences.

Here you find all the data sets described and analysed in the textbook: "Complex Networks: Principles, Methods and Applications", V. Latora, V. Nicosia, G. Russo (Cambridge University Press, 2017) For each data set you find below a brief description and a list of salient properties (number of node, number of edges, etc.). All data sets All the data sets of the textbook are available for download in a single compressed file: All the data sets in the book (zip) The archive contains one folder for each dataset, The file README.txt in each folder contains some relevant information about the corresponding data set.

复杂网络中基本网络模型的matlab实现.rar 随机网络，小世界网络以及无标度网络的构建算法。计算聚类系数和平均路径长度

该程序可以生成无标度网络，并可以计算网络的度分布及聚集系数．复杂网络 complex network基本参数计算 边权重计算 根据定义不同 可以选择不同的计算方法可变聚类无标度网络源代码

ER随机网络 当p不太小时， 聚集系数较小， 平均最短路径较短。

NetLogo是一个用来对自然和社会现象进行仿真的可编程建模环境。它是由Uri Wilensky在1999年发起的，由连接学习和计算机建模中心（CCL）负责持续开发。

十年之前（1998年6月4日），Nature发表了两位年轻的物理学家（D. J. Watts and S. H. Strogatz）关于网络的一篇论文。一年多之后（1999年10月15日），Science又发表了另外两位年轻的物理学家（A. L. Barabasi and R. Albert）关于网络的另一篇论文。这两篇论文引发了关于复杂网络的研究热潮。这个潮流席卷全球，涉及数学、力学、物理学、计算科学、管理科学、系统科学、社会科学、金融经济科学等许多科学领域，以及交通运输、能源传输、通讯工程、电子科学，甚至医学、烹饪等许多应用学科。至今(2008年3月)为止，D. J. Watts and S. H. Strogatz的论文被SCI收录的论文引用5670次；A. L. Barabasi and R. Albert的论文被引用3275次。

十年之前（1998年6月4日），Nature发表了两位年轻的物理学家（D. J. Watts and S. H. Strogatz）关于网络的一篇论文。一年多之后（1999年10月15日），Science又发表了另外两位年轻的物理学家（A. L. Barabasi and R. Albert）关于网络的另一篇论文。