Quantum Theory, Decision Making and Social Dynamics (Uncertainty, Computational Techniques, and Decision Intelligence). This item is unavailable.Quantum Theory, Decision Making and Social Dynamics (Uncertainty, Computational Techniques, and Decision Intelligence)

Quantum Theory, Decision Making, and Social Dynamics is a detailed exploration of the connection between quantum theory, decision-making, and social networks. As quantum theory expands into various fields, there is an increasing demand for accessible resources that clarify its principles and uses. This book aims to address that need by explaining the complex relationship between quantum theory and social dynamics, especially in decision-making contexts. It discusses the challenges of understanding and applying quantum theory in social settings and provides readers with the knowledge to leverage its potential in decision-making processes. The book is divided into eleven chapters, each focusing on a specific aspect of quantum theory and its applications. Chapter 1 introduces quantum theory, fuzzy logic, and social network analysis, highlighting key concepts like superposition, entanglement, and fuzzy influence within networks. Chapter 2 examines fuzzy sets, membership functions, and inference systems, with applications in devices, traffic management, and healthcare. Chapter 3 covers the mathematical framework of quantum mechanics and its philosophical paradoxes, connecting them to fuzzy logic models of uncertainty. Chapter 4 links social networks to quantum graphs, defining their topology, centrality, and entangled edges. Chapter 5 models social identity as a fuzzy quantum superposition, exploring identity collapse and coherence within networks. Chapter 6 relates quantum entanglement to social ties, proposing fuzzy–quantum graph models for interconnected systems. Chapter 7 analyses measures of irregularity in quantum graphs and applies these to financial networks. Chapter 8 integrates quantum cognition with fuzzy MCDM, employing various probability evaluation methods. Chapter 9 features case studies of fuzzy systems and their integration with quantum fuzzy graphs. Chapter 10 develops a quantum graph-based link prediction model for dynamic social networks. Chapter 11 concludes with a summary of the quantum–fuzzy framework, discussing its contributions, limitations, and future directions.

• Integrated Framework – Combines quantum theory, fuzzy logic, and social network analysis for modeling uncertainty and complexity.
• Novel Models – Presents quantum graphs, fuzzy–quantum identity, and entanglement-based social network representations.
• Real-World Applications – Includes practical case studies in decision-making, network analysis, and predictive modeling.

Tofigh Allahviranloo is a full professor of applied mathematics at Istinye University, Turkey. As a trained mathematician and computer scientist, Prof. Allahviranloo has developed a passion for multi- and interdisciplinary research. He is not only deeply involved in fundamental research in fuzzy applied mathematics, especially fuzzy differential equations, but he also aims at innovative applications in the applied biological sciences. He is the author of several books and many papers published by Elsevier and Springer. He actively serves the research community, as Editor-in-Chief of the International J. of Industrial Mathematics, and Associate Editor or editorial board member of several other journals, including Information Sciences, Fuzzy Sets and Systems, Journal of Intelligent and Fuzzy Systems, Iranian J. of Fuzzy Systems and Mathematical Sciences.

Sovan Samanta is an assistant professor in the Department of Mathematics, Tamralipta Mahavidyalaya, India and scientific advisor of Algebra Bernays University, Gradiscanska, Zagreb, Croatia. He is also a Visiting Professor at Instiya University, Turkey. Before that, he worked as an Assistant Professor in the Department of Basic Sciences at the Indian Institute of Information Technology, Nagpur. He holds a PhD in algebraic fuzzy graph theory from Vidyasagar University, India and a Post Doc in discrete mathematics from Hanyang University, South Korea. He has published over 87 papers in international journals, including 65 in SCIE/SCI journals. He has also authored and edited several books and book chapters, and serves as an Associate Editor for the Journal of Applied Mathematics and Computing, the Journal of Intelligent & Fuzzy Systems, and Mathematical Problems in Engineering.

Prasenjit Mandal is a scientific advisor of Algebra Bernays University, Gradiscanska, Zagreb, Croatia. He earned his Bachelor of Science degree with honors in Mathematics from Vidyasagar University in Paschim Medinipur, West Bengal, and his Master of Science degree in Mathematics from Guru Ghasidas Central University. He holds a PhD from Vidyasagar University. He has published 17 papers in SCI/SCIE-indexed journals, three papers in SCOPUS-indexed journals, and 10 papers in UGC CARE-listed journals. Recently, he was included in the AD Scientific Index - World Scientists Rankings. His research interests encompass group decision-making, soft computing, applied soft computing, rough sets, fuzzy algebra, and social networking-based decision-making.

Rupkumar Mahapatra is a scientific advisor of Algebra Bernays University, Gradiscanska, Zagreb, Croatia. He received his Bachelor of Science degree with honours in Mathematics from Vidyasagar University, Paschim Medinipur, West Bengal, India, and a Master of Science degree in Mathematics from Guru Ghasidas Central University. He holds a PhD from Vidyasagar University. Dr. Mahapatra has published 10 papers in SCI/ SCIE-indexed and one paper in SCOPUS-indexed journals. He is recently included in the list of AD Scientific Index- World Scientists Rankings. His research interests include Graph Theory, Fuzzy Graphs, and Social Networks.