Title: Proceedings of The Fifth France's International Conference on Complex Systems (FRCCS 2025): Advances in Complex Systems Science, Machine Learning, and . in Systems, Decision and Control, 615)
Publisher: Springer
Publication Date: 2025
Language: English
ISBN 10: 3032002052
ISBN 13: 9783032002051
Binding: Hardcover
Condition: New

About this title

Synopsis

This volume gathers the peer-reviewed proceedings of the Fifth France's International Conference on Complex Systems (FRCCS 2025), held in Bordeaux, France. FRCCS has become a key interdisciplinary venue for researchers and practitioners exploring the theory, modeling, and applications of complex systems.
The book covers a broad range of topics, including network science, dynamical systems, data mining, machine learning, computational social science, and complex urban and biological systems. Contributions highlight both theoretical advances and innovative applications across scientific, industrial, and societal contexts.
This collection will be a valuable reference for academics, engineers, and professionals working to understand, model, and manage complexity in real-world systems.

About the Author

Hocine Cherifi is a Professor at the University of Burgundy, France. His research interests span complex networks, explainable AI, and complex systems science. He is the Editor-in-Chief of PLOS Complex Systems and has been actively fostering the global complex systems community.

Jean-Loup Guillaume is Professor at Universit� de La Rochelle, France. His work focuses on network science, graph theory, and applications of complex systems in computational and data-driven domains.

Guy Melan�on is Professor at Universit� de Bordeaux, France. He conducts research in network visualization, complex data analysis, and the development of methodologies for exploring large-scale complex systems.

Bruno Pinaud is a Professor at Universit� de Bordeaux and a researcher at LaBRI. His work centers on data mining, network analysis, and the design of interactive tools for understanding complex data.

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