Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving (Paperback)

Predrag S. Stanimirovic

ISBN 10: 3032244013 / ISBN 13: 9783032244017

Published by Springer Nature Switzerland AG, Cham, 2026

About this Item

Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9783032244017

Bibliographic Details

• Title: Hybrid Methods for Modeling and Optimizing Complex Systems: Advances in Interdisciplinary Approaches for Complex Problem Solving (Paperback)
• Publisher: Springer Nature Switzerland AG, Cham
• Publication Date: 2026
• Language: English
• ISBN 10: 3032244013
• ISBN 13: 9783032244017
• Binding: Paperback
• Condition: new

About this title

Synopsis

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.