New Advances in Complex Networks with Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 932
Editor
Special Issue Information
Dear Colleagues,
Complex networks have emerged as a fundamental paradigm for understanding interconnected systems across diverse domains, from biological networks and social media to transportation infrastructures and financial markets. The challenge of analyzing and predicting the behavior of complex networks involves addressing multiple dimensions of complexity, including structural heterogeneity, temporal dynamics, and multi-layer interactions, which together determine the emergent properties of networked systems. Despite significant progress in network science, fundamental questions regarding network resilience, controllability, and the interplay between structure and dynamics remain partially unresolved in many network theories, such as scale-free network theory, small-world network theory, temporal network theory, multilayer network theory, and higher-order network theory. Particularly, while centrality measures, community detection algorithms, and network embedding techniques have been extensively developed and applied, their theoretical foundations and performance guarantees under various network conditions are not fully established in most cases. Rigorous mathematical frameworks and empirical validations, whether through analytical derivations or real-world applications, are essential for advancing our understanding of complex networks, similar to what has been achieved for random graph models, preferential attachment mechanisms, and percolation theory.
This Special Issue aims to serve as a platform for presenting cutting-edge theoretical developments, methodological innovations, and practical applications in complex network research. We particularly welcome contributions on network dynamics, machine learning on graphs, network resilience and robustness, community structure analysis, network controllability, and interdisciplinary applications that demonstrate the power of network approaches in solving real-world problems.
Dr. Yang Liu
Guest Editor
Manuscript Submission Information
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Keywords
- complex networks
- network dynamics
- multilayer networks
- network resilience
- community detection
- graph neural networks
- temporal networks
- network controllability
- network embedding
- higher-order interactions
- network science applications
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