Quantifying complexity and measuring structure within complex systems

量化复杂性并测量复杂系统中的结构

• 批准号: DP140100203
• 负责人: Prof Michael Small
• 金额: $ 18.88万
• 依托单位: The University of Western Australia
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140100203
• 关键词: Quantifying; complexity; measuring; structure; within

Most interesting systems are complex. The complex systems of interest in this project are characterised by a simple dynamical behaviour on each individual part; and a complicated web of interaction between the many distinct parts. The project will focus on the massive system of interacting neurones in the brain, and transmission of influenza via interpersonal contacts. This project will provide a better model of that web of interactions; and new methods for statistically validating this model against data. Existing models of complex networks are statistically biased so, by employing robust statistical methodologies, this problem will be rectified and provide a method for randomly choosing representative complex systems.

最有趣的系统都是复杂的。该项目中感兴趣的复杂系统的特点是每个单独部分都有简单的动态行为；以及许多不同部分之间复杂的相互作用网络。该项目将重点研究大脑中相互作用的神经元的庞大系统，以及流感通过人际接触的传播。该项目将为该交互网络提供更好的模型；以及根据数据统计验证该模型的新方法。现有的复杂网络模型存在统计偏差，因此，通过采用稳健的统计方法，这个问题将得到纠正，并提供一种随机选择代表性复杂系统的方法。