Uncertainty Propagation Methods for Networked Complex Systems

网络复杂系统的不确定性传播方法

• 批准号: 1301235
• 负责人: Rahul Rai
• 金额: $ 41.06万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1301235&HistoricalAwards=false
• 关键词: Uncertainty; Propagation; Methods; Networked; Complex

The objective of this research is development of a novel class of uncertainty quantification methods for networked complex systems. The fundamental and challenging uncertainty quantification problems remain unsolved, in particular combating the curse of dimensionality and solving uncertainty quantification problems related to large and multi-scale dynamic networks underlying modern day complex systems. The main challenge that lies at the core of analyzing and synthesizing the dynamic networks at the crux of modern day complex systems is: How do a collection of dynamical systems coupled through a dense wiring topology behave as a unit in the presence of uncertainty? The UB-SUNY team is developing of a suite of novel computational uncertainty quantification methods to tackle the main challenge and to enable accelerated design and deployment of complex systems.This project will have far reaching impacts on research and the practice of complex system design and management across a wide variety of industries. Development of these methods will have an immediate impact on the community at large with beneficiaries ranging from ordinary users to system design teams in industrial, and academic environments. Our research is being integrated into the education of graduate, undergraduate and high-school students including under-represented minorities in science and engineering fields. These educational activities involve: 1) developing workshops and short course for researchers and professionals working in the area of systems engineering and uncertainty quantification, 2) developing seminar courses for undergraduates, and 3) incorporation of research results in graduate/undergraduate courses.

这项研究的目的是开发一类新型的网络复杂系统的不确定性量化方法。基本且具有挑战性的不确定性量化问题仍未解决，特别是对抗维度灾难和解决与现代复杂系统底层的大型和多尺度动态网络相关的不确定性量化问题。分析和综合现代复杂系统关键动态网络的核心挑战是：通过密集布线拓扑耦合的动态系统集合在存在不确定性的情况下如何作为一个单元表现？ UB-SUNY 团队正在开发一套新颖的计算不确定性量化方法，以应对主要挑战并加速复杂系统的设计和部署。该项目将对各行业的复杂系统设计和管理的研究和实践产生深远的影响。这些方法的开发将对整个社区产生直接影响，受益者范围从普通用户到工业和学术环境中的系统设计团队。我们的研究正在融入研究生、本科生和高中生的教育，包括科学和工程领域代表性不足的少数群体。这些教育活动包括：1）为系统工程和不确定性量化领域的研究人员和专业人员开发讲习班和短期课程，2）为本科生开发研讨会课程，3）将研究成果纳入研究生/本科生课程。