整合B-to-B贸易网络模型的结构演变和货币流,重现所有主要的经验定律
Jun'ichi Ozaki1, Eduardo Viegas1,2, Hideki Takayasu1,3
1Department of Computer Science, School of Computing, Tokyo Institute of Technology, 4259, Nagatsuta-cho, Midori-ku, Yokohama, 226-8503, Japan.
Scientific reports
|February 26, 2024
概括
我们开发了一种新的两层模型,将网络结构和资金流联系起来. 这个框架准确地复制了现实世界的交易网络动态和代理行为,为金融政策预测提供了潜力.
科学领域:
- 复杂系统科学 复杂系统科学
- 网络科学 网络科学
- 基于代理的建模模型.
背景情况:
- 现有的模型经常孤立地研究网络拓和代理行为.
- 了解网络结构和代理级动态之间的相互作用对于复杂系统分析至关重要.
研究的目的:
- 开发一个统一的双层模型,整合时间网络结构和货币运输流.
- 解释微级代理动态如何在复杂网络中产生宏级统计属性.
- 通过使用来自日本的真实世界公司间交易数据来验证模型.
主要方法:
- 一个双层模型框架,连接网络拓和货币交易.
- 分析复杂网络中的集体运动动态.
- 模型生成的统计分布与来自日本企业间交易网络的实证数据的时间比较.
主要成果:
- 该模型成功地复制了网络和代理量的统计性质.
- 观察到网络中出现了帐形的增长率分布和缩放性质.
- 模型的输出与来自现实世界的交易数据的七个经验定律密切匹配.
结论:
- 开发的模型提供了一种统一的方法来理解复杂的网络动态.
- 该框架准确地捕捉了网络结构和代理行为之间的相互作用.
- 该模型显示出作为金融和审慎政策制定预测工具的潜力.
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