Topic Editors

Department of Computer Science and Technology, Ocean University of China, Qingdao 266100, China
Prof. Dr. Xiao-Zhi Gao
Faculty of Natural Sciences and Forestry, Department of Computer Science, University of Eastern Finland, 70211 Kuopio, Finland
Dr. Ying Tian
College of Information Technology, Jilin Agricultural University, Changchun 130118, China

Advances in Natural Computing: Methods and Applications

Abstract submission deadline
30 April 2026
Manuscript submission deadline
30 June 2026
Viewed by
15

Topic Information

Dear Colleagues,

Natural computing, as a cutting-edge computational paradigm, has made significant progress in both theoretical research and practical applications in recent years. Drawing inspiration from natural phenomena, biological mechanisms, and physicochemical processes, it has developed nature-inspired computational models and meta-heuristic algorithms, providing innovative solutions for complex problems that are challenging for traditional computing methods. These approaches harness principles such as evolution, swarm intelligence, self-organization, and adaptability, enabling breakthroughs in optimization, learning, and system design. Research in natural computing not only advances computer science but also fosters interdisciplinary collaborations with fields like artificial intelligence, bioinformatics, physics, and quantum computing, demonstrating vast potential for cross-domain innovation. We welcome submissions on topics including but not limited to the following: Theoretical foundations of natural computing, including nature-inspired models and the development of novel meta-heuristic algorithms. Applications of natural computing in artificial intelligence (e.g., neural networks, reinforcement learning). Applications in bioinformatics (e.g., sequence analysis, protein structure prediction). Meta-heuristic algorithms for optimization problems in engineering, logistics, and industry. Synergies between natural computing and quantum computing. The modeling and analysis of complex systems using nature-inspired approaches. By integrating nature-inspired principles and meta-heuristic strategies, this Topic aims to highlight advancements that bridge computational theory with real-world challenges. We encourage contributions that explore both foundational innovations and practical implementations.

Prof. Dr. Gaige Wang
Prof. Xiao-Zhi Gao
Dr. Ying Tian
Topic Editors

Keywords

  • natural computing
  • evolutionary algorithms
  • swarm intelligence
  • quantum-inspired computing
  • neural networks
  • healthcare applications
  • environmental modeling

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
AI
ai
3.1 7.2 2020 18.9 Days CHF 1600 Submit
Algorithms
algorithms
1.8 4.1 2008 18.9 Days CHF 1600 Submit
Applied Sciences
applsci
2.5 5.3 2011 18.4 Days CHF 2400 Submit
Electronics
electronics
2.6 5.3 2012 16.4 Days CHF 2400 Submit
Mathematics
mathematics
2.3 4.0 2013 18.3 Days CHF 2600 Submit
AppliedMath
appliedmath
- - 2021 25.3 Days CHF 1000 Submit

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