人与人接触动态的连续时间过程
Robin Persoons1, Matteo D'Alessandro1, Piet Van Mieghem1
1Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, P.O. Box 5031, 2600 GA Delft, The Netherlands.
Physical review. E
|October 21, 2025
概括
我们介绍了人类接触动态的连续时间马尔科夫模型,连续随机步行者诱导时间图模型 (CRWIG). 这种模型捕捉到复杂的人类移动模式,包括任意的飞行和暂停时间,与非马科夫扩展.
科学领域:
- 复杂的系统复杂的系统.
- 网络科学 网络科学
- 随机过程 随机过程
背景情况:
- 人与人接触的动态对于了解疾病传播和社会互动至关重要.
- 现有的模型往往简化了移动模式,限制了它们在现实世界中的适用性.
研究的目的:
- 为人类接触动态开发一种新的连续时间马尔科夫模型.
- 分析步行者相互作用和接触图形形成的新兴特性.
- 扩展模型的非马科夫行为,并与经验人类流动性数据进行比较.
主要方法:
- 连续随机步行者诱导时间图 (CRWIG) 模型的开发.
- 对于步行者组合的马尔科夫治理方程的数学公式.
- 时间离散效应的分析和指数式衰变和交集时间尾巴的证明.
- 扩展到一个非马科夫模型,具有非指数的逗留时间.
主要成果:
- CRWIG 显示了初始条件的指数式衰变和指数式缩短的会议间隔时间.
- 非马科夫扩展精确地重现了人类的实证移动性:任意的飞行/暂停分布.
- 扩展模型产生了权力定律与指数尾巴之间的时间分布.
结论:
- CRWIG模型为研究人与人接触动态提供了一个强大的框架.
- 非马科维的扩展显著提高了模型捕捉现实世界人类流动的能力.
- 这项工作为流行病学,城市规划和社交网络分析等领域提供了宝贵的见解.
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