Special Issues
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Modelling, Analysis, and Control of Complex Networks for Multi-Domain Coupled Systems: Theory and Applications

Submission Deadline: 31 August 2026 View: 27 Submit to Special Issue

Guest Editors

Prof. Dr. Liang'an Huo

Email: huohuolin@yeah.net

Affiliation: Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China

Homepage:

Research Interests: artificial intelligence, emergency management, public opinion propagation

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Dr. Yingying Cheng

Email: yingying_cheng@haust.edu.cn

Affiliation: Business School, Henan University of Science and Technology, Luoyang, 471023, China

Homepage:

Research Interests: emergency management, information propagation, logistics, and supply chain management

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Summary

Complex networks serve as a core tool for characterizing coupled relationships across domains, like social interactions, information diffusion, and risk evolution. Yet, cross-domain systems face challenges in describing coupling mechanisms, predicting transmission paths, and coordinating control strategies. Targeted modelling, transmission law analysis, and precise control based on complex networks are thus crucial for optimizing social governance and enhancing risk resistance.


This special issue focuses on Modeling, Analysis, and Control of Complex Networks: From Theory to Applications. The following subtopics are the particular interests of this special issue, including but not limited to:
1. Dynamic modeling of multi-domain coupled systems under complex networks (e.g., multi-agent network models integrating social interaction, information flow, and risk evolution)
2. Transmission mechanisms and path optimization of heterogeneous content (information, knowledge, rumors, emotions) in complex networks
3. Risk transmission assessment and early warning methods for complex networks under extreme scenarios (public events, sudden disasters)
4. Multi-domain coordinated control strategies based on complex network characteristics (e.g., linked optimization of information guidance and risk prevention and control)
5. Data-driven inversion of complex network transmission parameters and simulation of control effects (e.g., transmission trend prediction integrating multi-source data)
6. Differential characteristics and regulation schemes of element transmission in special groups or network structures (e.g., community networks, hierarchical networks)


Keywords

complex networks, multi-domain coupled systems, dynamic modelling, transmission mechanisms, risk assessment and early warning, coordinated control strategies, cross-scenario applications

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