Complex networks can be seen everywhere such as biology, chemistry, ecology, economics, physics, and even the Internet. There are many achievements in complex networks based on varied theories and models from mathematics and physics as well. However, the structures and internal properties of complex networks which lead to the major applications in sciences and technologies are still worth exploring. Among them, Computational Intelligence (CI) methodologies can be greatly contributed to solve these issues, in particular, the dynamics of complex networks. Applications of these CI methods to model and simulate complex networks are the main focus of this special session. The scope of the methodologies and ideas may include neural networks, artificial immune systems, swarm intelligence, fuzzy systems and other CI methods or general approaches from applied mathematics, physics, bio-inspired methodologies and control theory.
Scope and Topics
Topics of interest include but are not limited to:- analysis and visualization of complex networks
- artificial immune systems
- big data and complex networks
- chaos in complex networks
- complex adaptive networks
- complex networks and self-organization
- control and dynamics of complex networks
- dynamics of complex networks
- mathematical modelling and analysis of complex networks
- modelling and simulation of biological networks
- robustness and stability of complex networks
- scale-free complex networks
- swarm intelligence and complex networks
- small-world complex network
- statistical properties of complex networks
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