- 中图分类号: O1
- 语种: ENG
- 出版信息: Wiley 2013 330页
- EISBN: 9781118762806
- PISBN-P: 9781118534502
- 原文访问地址:
KG评星
知识图谱评星,是一种基于用户使用的评价体系,综合图书的评论数量、引文数量、Amazon评分以及图谱网络中节点的PageRank值(即考虑相邻节点数量和重要性)等多种因素计算而得出的评价数值。星级越高,推荐值越高。CAT核心级
核心学术资源(CAR)项目作为教图公司推出的一项知识型服务,旨在打造一套科学、有效的图书评价体系,并协助用户制定相应的馆藏建设方案。CAR项目调查和分析12所世界一流大学的藏书数据,以收藏学校的数量确定书目的核心级,核心级越高,代表书目的馆藏价值越高。选取核心级在三级以上,即三校以上共藏的图书作为核心书目(CAT)。Explores the emerging subject of epidemic dynamics on complex networks, including theories, methods, and real-world applications Throughout history epidemic diseases have presented a serious threat to human life, and in recent years the spread of infectious diseases such as dengue, malaria, HIV, and SARS has captured global attention; and in the modern technological age, the proliferation of virus attacks on the Internet highlights the emergent need for knowledge about modeling, analysis, and control in epidemic dynamics on complex networks. For advancement of techniques, it has become clear that more fundamental knowledge will be needed in mathematical and numerical context about how epidemic dynamical networks can be modelled, analyzed, and controlled. This book explores recent progress in these topics and looks at issues relating to various epidemic systems. Propagation Dynamics on Complex Networks covers most key topics in the field, and will provide a valuable resource for graduate students and researchers interested in network science and dynamical systems, and related interdisciplinary fields. Key Features: Includes a brief history of mathematical epidemiology and epidemic modeling on complex networks. Explores how information, opinion, and rumor spread via the Internet and social networks. Presents plausible models for propagation of SARS and avian influenza outbreaks, providing a reality check for otherwise abstract mathematical modeling. Considers various infectivity functions, including constant, piecewise-linear, saturated, and nonlinear cases. Examines information transmission on complex networks, and investigates the difference between information and epidemic spreading.