Innovative Approaches to Modeling Complex Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".

Deadline for manuscript submissions: 10 September 2025 | Viewed by 1886

Special Issue Editors


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Guest Editor
Department of Basic Sciences, Ernst-Abbe University of Applied Sciences Jena, Carl-Zeiss-Promenade 2, 07745 Jena, Germany
Interests: mathematics; dynamical systems; renewable energies; reaction networks; virus infection dynamics modeling

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Guest Editor
1. College of Arts & Sciences, Mathematics & Natural Science Department, Gulf University for Science and Technology, Hawally, Kuwait
2. Institute of Bioinformatics, Friedrich Schiller University Jena, Jena, Germany
3. The European Virus Bioinformatics Center, Jena, Germany
Interests: mathematical and computational systems biology; multiscale and unconventional modelling, simulation, and analysis of complex systems
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Special Issue Information

Dear Colleagues,

The forthcoming Special Issue, titled “Innovative Approaches to Modeling Complex Systems”, seeks to showcase groundbreaking methodologies that push the boundaries of traditional modeling techniques. These innovative approaches have emerged to overcome the challenges inherent in conventional methods, particularly when addressing the complexities of high-dimensional reaction networks, emergent behaviors, and a significant number of unknown parameters.

Complex systems, prevalent across diverse fields such as biology, ecology, economics, and the social sciences, pose unique challenges due to their intricate, non-linear dynamics and emergent properties. This Special Issue aims to highlight modeling techniques that break away from established paradigms, offering fresh perspectives and effective solutions for understanding and predicting the behavior of such systems. Contributions to this Special Issue are expected to cover a wide range of topics, and they include, but are not limited to, the following:

  • Agent-based modeling and simulation;
  • Rule-based modeling for dynamic systems;
  • Network theory and complex network analysis;
  • Fractal analysis;
  • Machine learning and artificial intelligence;
  • Computational and human intelligence;
  • Explorations in complex system dynamics;
  • Unconventional modeling and simulations;
  • Innovative methodologies in differential equations;
  • Hybrid systems of differential equations.

We invite researchers and practitioners to submit original research articles, reviews, and perspectives that explore innovative modeling approaches, novel methodologies, and their practical applications in understanding and predicting the behavior of complex systems. Contributions that propose new paradigms or explore interdisciplinary applications are particularly encouraged. By uniting contributions from diverse disciplines, this Special Issue aims to push the boundaries of complex system modeling, advancing the field while fostering interdisciplinary collaboration to address some of the most pressing challenges of the modern world.

Dr. Stephan Peter
Prof. Dr. Bashar Ibrahim
Guest Editors

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Keywords

  • complex systems
  • nonlinear dynamics
  • chaos theory and fractals
  • dynamical systems and network theory
  • differential equations (including hybrid and unconventional forms)
  • discovery science and knowledge discovery
  • transfer learning and adaptive models
  • context-driven approaches
  • data mining and information extraction
  • intuitive modeling approaches

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Published Papers (1 paper)

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Review

12 pages, 2066 KiB  
Review
Intuitive Innovation: Unconventional Modeling and Systems Neurology
by Stephan Peter and Bashar Ibrahim
Mathematics 2024, 12(21), 3308; https://doi.org/10.3390/math12213308 - 22 Oct 2024
Cited by 1 | Viewed by 1519
Abstract
This review explores how intuitive processes drive innovation, which we define as novel ideas, inventions, or artistic creations that cannot be logically derived from existing knowledge or sensory data. Although intuitive processes are not yet fully recognized as a formal area of scientific [...] Read more.
This review explores how intuitive processes drive innovation, which we define as novel ideas, inventions, or artistic creations that cannot be logically derived from existing knowledge or sensory data. Although intuitive processes are not yet fully recognized as a formal area of scientific research, this paper examines current approaches to their study and modeling. It highlights the necessity of integrating unconventional modeling methods with neuroscience to gain deeper insights into these processes. Key experimental studies investigating extrasensory abilities—such as remote viewing, precognition, and telepathy—are reviewed, emphasizing their potential relevance to innovation. We propose that combining these unconventional modeling approaches with insights from systems neurology can provide new perspectives on the neural mechanisms underpinning intuition and creativity. This review emphasizes the critical need for further research into intuitive processes to address complex global challenges. It calls for a more open, interdisciplinary approach to scientific inquiry, promoting the exploration of unconventional forms of knowledge generation and their neural correlates. Full article
(This article belongs to the Special Issue Innovative Approaches to Modeling Complex Systems)
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