Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving
Redigert av Jajati Keshari Sahoo, Spyridon D. Mourtas, Predrag S. Stanimirovic, 2026.Del av serien Lecture Notes in Networks and Systems.
Proceedings of the IV International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-IV 2025), Volume 1
This volume presents selected papers from the IV International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems, introducing hybrid methodologies integrating mathematical modeling, machine learning, and intelligent optimization to enhance prediction, analysis, and decision-making. The volume covers hybrid modeling and optimization, AI-driven monitoring systems, cybersecurity and data protection, blockchain infrastructures, logistics and manufacturing integration, as well as advances in data mining, recommender systems, reinforcement learning, pattern recognition, and adaptive intelligence using evolutionary algorithms and neural networks. Combining theoretical advances with applied case studies, the book demonstrates how hybrid methods improve predictive accuracy, system efficiency, and intelligent decision support. It is intended for researchers, engineers, data scientists, and graduate students working with complex systems and artificial intelligence.
Språk: Engelsk
Oppdag mer
Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving
Redigert av Jajati Keshari Sahoo, Spyridon D. Mourtas, Predrag S. Stanimirovic, 2026.Del av serien Lecture Notes in Networks and Systems.
Proceedings of the IV International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems (HMMOCS-IV 2025), Volume 1
This volume presents selected papers from the IV International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems, introducing hybrid methodologies integrating mathematical modeling, machine learning, and intelligent optimization to enhance prediction, analysis, and decision-making. The volume covers hybrid modeling and optimization, AI-driven monitoring systems, cybersecurity and data protection, blockchain infrastructures, logistics and manufacturing integration, as well as advances in data mining, recommender systems, reinforcement learning, pattern recognition, and adaptive intelligence using evolutionary algorithms and neural networks. Combining theoretical advances with applied case studies, the book demonstrates how hybrid methods improve predictive accuracy, system efficiency, and intelligent decision support. It is intended for researchers, engineers, data scientists, and graduate students working with complex systems and artificial intelligence.
Oppdag mer
Språk: Engelsk
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