Mathematical model reduction for complex networks

复杂网络的数学模型简化

• 批准号: DP180101991
• 负责人: Prof Georg Gottwald
• 金额: $ 22.85万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2018
• 资助国家: 澳大利亚
• 起止时间: 2018-03-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP180101991
• 关键词: Mathematical; model; reduction; complex; networks

This project aims to develop new mathematical methodology to describe the collective behaviour of large networks of oscillators with parameters called collective coordinates. This will allow for the quantitative description of finite-size networks as well as chaotic dynamics, which are both out of reach for current model reduction methods. The project will apply methodology to understand the causes of, and ways to prevent, glitches and failure in the emerging modern decentralised power grids. This will develop a framework to address this question, tailored to deal with the hitherto uncharted case of finite-size networks.

该项目旨在开发新的数学方法，用称为集体坐标的参数来描述大型振荡器网络的集体行为。这将允许对有限大小的网络和混沌动力学进行定量描述，而这两者都不是目前的模型简化方法所能达到的。该项目将应用方法论来了解新兴的现代分散电网中故障和故障的原因以及预防方法。这将开发一个框架来解决这个问题，专门为处理迄今未知的有限大小网络情况而量身定做。