SBE: Small: Statistical Models and Methods for Dynamic Complex Networks

SBE：小型：动态复杂网络的统计模型和方法

• 批准号: 1523785
• 负责人: Harry Crane
• 金额: $ 27.82万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1523785&HistoricalAwards=false
• 关键词: SBE; Small; Statistical; Models; Methods

The project examines the structure and function of dynamic networks by formulating and analyzing probabilistic models for temporally evolving networks and processes occurring on them. In addition, the project seeks practical and efficient statistical methods for network inference. The project is primarily motivated by national security concerns surrounding counter-terrorism and cybersecurity, but outcomes should be directly relevant in biological, social, and physical science applications as well as mathematical areas of probability theory, combinatorics, and graph theory. Cybersecurity and counter-terrorism efforts motivate three main technical objectives: (I) to establish a mathematical theory that explains both structural phenomena and temporal dependence in real world networks, (II) to develop efficient computational techniques for inferring networks from data, and (III) to analyze how structural changes affect processes that occur on networks, such as spread of disease, epidemic thresholds, and dissemination of information. Achievement of these outcomes will rely on computational tools as well as mathematical techniques from combinatorics, algebra, percolation theory, probability, and statistics

该项目通过制定和分析时间演变网络和过程的概率模型来检查动态网络的结构和功能。此外，该项目还寻求实用和有效的网络推理统计方法。该项目的主要动机是围绕反恐和网络安全的国家安全问题，但成果应与生物，社会和物理科学应用以及概率论，组合学和图论的数学领域直接相关。网络安全和反恐工作激发了三个主要技术目标：（I）建立一种数学理论，解释真实的世界网络中的结构现象和时间依赖性，（II）开发从数据推断网络的有效计算技术，（III）分析结构变化如何影响网络上发生的过程，如疾病的传播，流行病阈值，和传播信息。 这些成果的实现将依赖于计算工具以及来自组合学、代数、渗流理论、概率和统计学的数学技术