Submission Deadline: 31 January 2027 View: 592 Submit to Special Issue
Prof. Dr. Jun Zhang
Email: junzhanghk@hanyang.ac.kr
Affiliation: Computational Intelligence Laboratory, Hanyang University ERICA Campus, Ansan, South Korea
Research Interests: computational intelligence, operations research
Assoc. Prof. Dr. Wei-Jie Yu
Email: yuweijie6@mail.sysu.edu.cn
Affiliation: School of Information Management, Sun Yat-sen University, Guangzhou, China
Research Interests: computational intelligence, evolutionary computation
Complex systems are central to many engineering and scientific domains, where high dimensionality, strong coupling, nonlinearity, uncertainty, and dynamic behaviors pose significant challenges to conventional modeling and optimization approaches. In recent years, computational intelligence has demonstrated substantial potential in addressing these challenges through adaptive learning, intelligent search, knowledge extraction, and robust decision-making. Methods such as evolutionary computation, swarm intelligence, neural networks, fuzzy systems, and soft computing have increasingly contributed to the analysis, modeling, optimization, and control of complex systems.
This Special Issue aims to present progress in theories, methodologies, algorithms, and applications of computational intelligence for complex systems. The scope covers both methodological innovations and application-oriented studies, with particular interest in intelligent modeling, large-scale and dynamic optimization, uncertainty management, hybrid intelligent frameworks, and decision-making in complex environments. We invite high-quality original research and review articles that push the boundaries of current computational intelligence capabilities and foster interdisciplinary collaboration.
Suggested themes include, but are not limited to:
· Computational intelligence for complex system modeling and analysis
· Evolutionary computation and swarm intelligence for complex optimization
· Neural networks, fuzzy systems, and soft computing methodologies
· Hybrid intelligence frameworks integrating learning, optimization, and reasoning
· Data-driven and physics-informed modeling of complex systems
· Distributed, parallel, and multi-agent computational intelligence
· Robust and uncertainty-aware intelligent methods
· Engineering and scientific applications of computational intelligence
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