分析复合极端事件的网络方法:高语音流量和高数据吞吐量事件中的风险增强关系和触发因果关系

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-10-15 DOI:10.1016/j.chaos.2024.115661
Li-Na Wang , Hao-Ran Liu , Yu-Wen Huang , Chen-Rui Zang , Jun Wang
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引用次数: 0

摘要

基于事件巧合分析(ECA)的思想,我们提出了一种网络分析方法来研究不同地理位置的复合极端事件。将网络模型与统计相关性研究相结合,可以分析这些事件之间潜在的风险增强关系和触发因果关系。在这种方法中,我们将不同的地理位置视为节点,当节点 i 处的事件 A 同步发生在节点 j 处的事件 B 之前时,构建一条从节点 i 到节点 j 的有向边。前兆重合分析量化了两类极端事件之间的风险增强关系,而触发重合分析则量化了两类极端事件之间的触发因果关系。根据这些事件在不同地理位置的统计相关性,可以构建一个有向加权网络。对网络拓扑特征的进一步分析扩展了传统 ECA 的方法和应用。在此,我们构建了高语音流量和高数据吞吐量的前兆功能网络和触发功能网络,以分析通信系统中不同基站的潜在风险增强和这些事件之间的触发因果关系。
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A network method to analyze compound extreme events: Risk enhancement relationship and trigger causal relationship in high voice traffic and high data throughput events
Based on ideas from event coincidence analysis (ECA), we propose a network analysis method to study compound extreme events at different geographical locations. Integrating network modeling into statistical correlation research allows us to analyze potential risk enhancement relationship and trigger causal relationship between these events. In this approach, we consider different geographical locations as nodes and construct a directed edge from node i to node j when event A at location i occurs synchronously before event B at location j. Precursor coincidence analysis quantifies the risk enhancement relationship between two types of extreme events, while trigger coincidence analysis quantifies the trigger causal relationship between two types of extreme events. A directed weighted network can be constructed based on statistical correlations between these events at different geographical locations. Further analysis of network topology characteristics extends traditional ECA in method and application. Herein, we construct the precursor functional network and the trigger functional network of high voice traffic and high data throughput to analyze potential risk enhancement and trigger causal relationships between these events at different base stations within a communication system.
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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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