This contributed volume provides an integrated perspective on modern mathematical and computational techniques for addressing complex problems in networks, control systems, learning, and game theory. It encompasses state-of-the-art research from a diverse range of disciplines, including dynamical systems, stochastic analysis, optimization, game theory, machine learning, and transportation theory. Particular emphasis is placed on connecting rigorous theoretical developments with real-world applications.

This volume is organized into twelve chapters. The first part (Chapters 1-6) addresses the optimal transportation problem in traffic networks. The second part (Chapters 7-11) investigates Markov chains with memory by examining the geometric, algebraic, dynamical, and ergodic properties of quadratic (polynomial) stochastic operators associated with cubic stochastic hypermatrices. Finally, Chapter 12 illustrates how methods from stochastic analysis and dynamical systems can be applied to lattice models of statistical mechanics defined on a Cayley tree.

Intended to serve as a comprehensive reference for academics and researchers, this volume may also benefit practitioners and anyone interested in exploring the interplay among these fields.

Covers theory and applications in dynamical systems, stochastic analysis, optimization, and more Focuses on the interplay between research fields to address real-world problems Gathers cutting-edge research from renowned experts

Autorentext

Mansoor Saburov is an Associate Professor at the Gulf University for Science and Technology. He received his PhD in Mathematics (2011) from the International Islamic University Malasia. His research interests lie in dynamical systems, functional analysis, quantum probability, and (p)-adic analysis.

Naira Hovakimyan is a Professor at the University of Illinois at Urbana-Champaign, USA. She received her PhD in Physics and Mathematics (1992) from the Institute of Applied Mathematics of the Russian Academy of Sciences. Her research interests include control and optimization, autonomous systems, machine learning, neural networks, and their applications.

Armen Badgasaryan is Researcher at the Institute of Mathematics of the National Academy of Sciences, Armenia, and Associate Professor at the Institute of Mathematics and Informatics of Russian-Armenian University, Armenia. He holds a Ph.D. in applied mathematics (2000) from the Russian Academy of Sciences. He does research in the fields of number theory, analysis, dynamical systems, optimization and control, and optimal transport.

Inhalt

• Bagdasaryan, A. Geometric, Dynamic, and Stochastic Analysis of Wardrop-Schur Optimal Transport Networks.- O'Neill, S. and Bagdasar, O. Classical and Novel Measures for Component Criticality in Selfish-Routing Networks.- Daher, W.; Damrah, S.; and Aydilek, H. Review of the Single-Period Kyle Model (1985).- Dingle, K. Curious Coincidences and Kolmogorov Complexity.- Medfouni, M.N.; Saber, M.; Korichi, K.; Marouf, N.; and Mabrouk, E. Predicting Solid Flow and Suspended Sediment Concentrations in a Semi-Arid Environment using Machine Learning and Deep Learning Approaches.- Azizi, S.P.; Nafei, A.; and Hamzi, B. EDM-2DSL: Calibrated Dynamical Modeling of Signal Decomposition Systems with Applications in Time Series Forecasting.- Saburov, M. On Ganikhodjaev Algebra of Cubic Matrices.- Ganikhodjaev, N. Quadratic Stochastic Operators: Ergodic Properties and Their Applications to Evolutionary Games and Economic Models.- Ganikhodjaev, N. and Zanin, D. Ergodic Volterra Quadratic Mappings of the Simplex.- Saburov, M.; Saburov, K.; and Saburov, K. Global Stability of Quadratic Stochastic Operators Associated with Column Primitive Cubic Doubly Stochastic Matrices.- Abdushukurov, A.A.; Muradov, R.S. Stochastic Analysis of Survival Functions Using Copulas and Its Applications.- Mukhamedov, F. and Khakimov, O. P-adic dynamical systems fo-models on the Cayley trees. <p