课程申请详细信息

课程代码 :

AU7001

课程名称 :

网络科学导论

课程英文名称 :

Network Science: An Introduction

课程简称:

类型 :

一级学科

开课学期:

秋季

学科/院系:

控制科学与工程

课程学分:

2

是否跨学期 :

否

总学时:

32

实验课学时 :

讨论学时 :

周学时 :

课程性质 :

专业课

课程层次 :

博士课程

课程分类 :

全日制课程

课程类型 :

（0811）控制科学与工程

考试方式:

上课方式:

课程教材语种类型:

授课语言类型:

成绩等级 :

通过不通过

是否绩点统计 :

否

开课状态 :

开课

任课老师:

课程简介 :

对各种复杂网络的定量与定性特征的科学理解已成为网络时代科学研究中一个极其重要的挑战性课题，网络科学就是一门正在兴起的面对这一挑战的交叉性学科。本课程在概要介绍网络科学的背景和研究意义之后，分为四个部分详细介绍网络基本概念、网络拓扑性质、网络拓扑模型和网络动力学。课程既注重网络科学的基本概念、思想和方法，也会适当介绍近期研究进展及一些有待解决的问题。通过本课程的学习，学生能够具备把网络科学方法用于实际网络分析的能力，包括"分析实际网络的拓扑性质"、"建立合适的网络模型"、"分析网络结构对网络行为的影响" 教师授课为主，每个学生团队也都需要在课堂上报告本项目完成情况。每3-4个学生组成一个团队，并自行选定研究课题。科学研究中的合作将会变得越来越重要，一个科研人员往往需要有很多的时间与不同的科研人员进行合作。因此，本课程特别鼓励同学们合作完成项目。

课程英文简介:

It has become a very challenging topic facing science research in the network era to have a scientifically understanding of the features of all kinds of networks in the real world, both qualitatively and quantitatively. Network science is just such an emerging interdisciplinary branch aims at facing the challenge. After a bird's eye view of the background of network science, the course will introduce in detail network basic concepts, network topological properties, network topology modeling and network dynamics. The course tries to introduce the basic concepts, ideas and methodologies of network science, as well as some recent advances and open problems. Upon completion of this course, the students will be able to apply basic knowledge of network science to various practical problems, which include o analyze the properties of real networks o build representative network models o analyze the effects of network structures on dynamical behaviors Lecturing is the core of teaching. Lectures will also involve a presentation of the projects in class by each group of 3-4 students, and it is largely up to the group to define the topic and scope of the project. Collaboration will be more and more important in science research, and a researcher will spend a significant amount of career working with different people. Thus, the course strongly encourages students to form groups to work together on the project.

教学大纲:

第一章引论 3 1.1 引言 1.2 网络时代的网络研究 1.3 网络时代的网络科学 1.4 课程内容简介第二章网络与图 4 2.1 引言 2.2 网络的图表示 2.3 图的计算机表示 2.4 共引与文献耦合 2.5 路径与连通性 2.6 生成树与最小生成树 2.7 二分图与匹配问题 2.8 稳定匹配第三章网络基本拓扑性质 4 3.1 引言 3.2实际网络的连通性 3.3 节点的度 3.4 平均路径长度 3.5 聚类系数 3.6 度分布 3.7 幂律分布第四章度相关性与社团结构 4 4.1 引言 4.2 度相关性与同配性 4.3 社团结构与模块度 4.4 基于模块度的社团检测算法 4.5 其它社团检测算法第五章节点重要性与相似性 4 5.1 引言 5.2 无向网络节点重要性指标 5.3 权威值和枢纽值：HITS算法 5.4 PR值：PageRank算法 5.5节点相似性与链路预测第六章随机网络模型 4 6.1 引言 6.2 从规则网络说起 6.3 随机图 6.4 广义随机图 6.5 随机重连与零模型 6.6 基于零模型的拓扑性质分析第七章小世界网络模型 4 7.1 引言 7.2 小世界网络模型 7.3 拓扑性质分析 7.4 Kleinberg模型与可搜索性 7.5 层次树结构网络模型与可搜索性第八章无标度网络模型 4 8.1 引言 8.2 BA无标度网络模型 8.3 Price模型 8.4 无标度网络模型的推广 8.5 鲁棒性与脆弱性第九章网络传播 4 9.1 引言 9.2 经典的传染病模型 9.3 几类网络的传播临界值分析 9.4 复杂网络的免疫策略 9.5 节点传播影响力分析 9.6 行为传播的实证研究第十章网络博弈 4 10.1 引言 10.2 博弈模型 10.3 规则网络上的演化博弈 10.4 小世界网络上的演化博弈 10.5 无标度网络上的演化博弈第十一章网络同步与控制 4 11.1 引言 11.2 网络同步判据 11.3 网络同步化能力分析 11.4 网络牵制控制 11.5 网络完全可控性

教学进度:

Ch. 1 Introduction 1.1 Introduction 1.2 Network research in the network era 1.3 Network science in the network era 1.4 A brief introduction of the course Ch. 2 Network and Graph 2.1 Introduction 2.2 Graph representation of network 2.3 Computer representation of graph 2.4 Co-citation and bibliographic couplng 2.5 Path and connectivity 2.6 Spanning tree and minimum spanning tree 2.7 bipartite graph and matching 2.8 Stable matching Ch.3 Basic Topological Properties of Networks 3.1 Introduction 3.2 Connectivity of real networks 3.3 Node degree 3.4 Average path length 3.5 Clustering coefficient 3.6 Degree distribution 3.7 Power law distribution Ch.4 Degree Correlation and Community Structure 4.1 Introduction 4.2 Degree correlation and assortativity 4.3 Community structure and modularity 4.4 Community detection algorithms based on modularity 4.5 Other community detection algorithms Ch. 5 Node Importance and Similarity 5.1 Introduction 5.2 Node importance indices for undirected networks 5.3 Hub and Authority: HITS algorithm 5.4 PR index: PageRank algorithm 5.5 Node similarity and link prediction Ch.6 Random Graph Models 6.1 Introduction 6.2 Regular networks 6.3 Random graph 6.4 Generalized random graph 6.5 Random rewiring and null model 6.6 Topological property analysis based on null model Ch. 7 Small-World Network Model 7.1 Introduction 7.2 Small-world network model 7.3 Topological property analysis 7.4 Kleinberg model and searchability 7.5 Hierarchical categorization scheme and searchability Ch. 8 Scale-Free Network Models 8.1 Introduction 8.2 BA scale-free network models 8.3 Price model 8.4 Generalized scale-free network models 8.5 Robustness and fragility Ch. 9 Spreading on Networks 9.1 Introduction 9.2 Classical epidemic models 9.3 Epidemic threshold analysis 9.4 Immunization on complex networks 9.5 Identification of influential spreaders 9.6 Empirical study on behavior spreading Ch. 10 Network Games 10.1 Introduction 10.2 Game models 10.3 Evolutionary game on regular networks 10.4 Evolutionary game on small-world networks 10.5 Evolutionary game on scale-free networks Ch. 11 Network Synchronization and Control 11.1 Introduction 11.2 Network synchronization criterion 11.3 Network synchronizability analysis 11.4 Network pinning control 11.5 Complete controllability of networks Project Presentation

考试大纲:

作业占40%，一个项目占60%