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    1. Ekonomi och Ledarskap
    2. Företagsekonomi

    Analytical and Computational Modeling of Complex Systems

    A Systematic Approach to Understanding Real-World Complexity

    AvFlorentin Paladi,Aleksandr A. Barsuk

    Häftad, Engelska, 2027

    1 722 kr

    Kommande

    Beskrivning

    Analytical and Computational Modeling of Complex Systems: A Systematic Approach to Understanding Real-World Complexity presents modern studies of complex systems by methods of statistical physics, numerical calculation, and computer modelling. Using general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, the authors present an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behaviour of the order parameter dependences on the control parameter (bifurcation diagrams). The existence of five canonical (normal) forms of bifurcations is shown, and the role of the intermediate metastable state in the kinetics of phase transitions is elucidated in the framework of these parametric models. The modelling is extended to multi-dimensional dynamical systems. Relations between the infinitesimal quantities of order parameters and the control of dynamical systems are given, and the formulae for the order parameter sensitivity are presented, depending on the variations in the control parameters. Stability analysis of the equilibrium states for nonlinear complex systems described by the Landau-type kinetic potential with two order parameters and the Lotka-Volterra model is conducted. Two different rate processes as combinations of in series and in parallel pathways are described. The peculiarities of the anomalous generation and extinction phenomenon of crystal nuclei at very low temperatures in non-equilibrium supercooled liquids are presented. Also, a robust methodology is applied to heterogeneous complex systems with stochastic interactions to optimize the distribution of particles among clusters, based on both the total number of particles in the system and the number of available states. In addition, the book presents an integrated approach that bridges stochastic modelling with computational agent-based models. Building on this foundation, the authors then introduce a unified probabilistic framework for modelling heterogeneous multi-agent interactions in complex systems that exhibit memory and adaptive learning. This approach (which appears phenomenological if it is not agent-based) can precisely describe the average outcomes of agent-based computations (where there is a lack of probabilistic insight). Developing such a framework, unlike conventional agent-based models, maintains analytical tractability through mean-field approximations, while capturing complex emergent behaviors. Models are validated using diverse real-world applications. The book also presents concepts and techniques used to model complex neural networks, biochemical reaction networks in cells, and the dynamic behaviour of economic systems over time. By balancing theoretical depth with intuitive explanations and practical applications, this book serves as both a learning resource and a practical reference for those engaged in the study of complex systems and their diverse real-world implementations. The book also offers a systematic learning path from theory to applications. It provides case studies that bridge the gap between mathematical formalism and complex systems modeling and simulation. Emphasizing hybrid and probabilistic modeling techniques, the book ensures greater flexibility for real-world applications. Covering a broad range of topics, it supports interdisciplinary use across departments such as physics, computer science, engineering, economics, and more.

    • Introduces a coherent methodology that integrates analytical techniques with probabilistic and computational approaches for modeling complex adaptive populations and dynamical systems, and offers real-world applications ranging from the physics of phase transitions and ecology to cellular processes and economic dynamical systems
    • Presents techniques for analysis of bifurcations and stability in complex thermodynamic systems near equilibrium parameter values, sensitivity analysis of equilibrium states in multi-dimensional dynamical systems, including general solution for phase transitions involving an intermediate metastable state
    • Helps readers develop transferable skills in system analysis, regardless of domain, and provides a dual approach that accommodates a wider audience, from mathematically oriented researchers to practitioners seeking applicable computational tools
    • Applied case studies and examples Include MATLAB and Python program code, along with their outputs, tables, and figures

    Produktinformation

    • Utgivningsdatum:2027-04-01
    • Mått:191 x 235 x undefined mm
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:250
    • Förlag:Elsevier Science
    • ISBN:9780443526695

    Utforska kategorier

    • Företagsekonomi inom Ekonomi och Ledarskap
    • Diskret matematik inom Naturvetenskap och teknik
    • Beräkning och matematisk analys inom Naturvetenskap och teknik

    Mer om författaren

    Dr. Florentin Paladi, Moldova State University, Department of Theoretical Physics, Chisinau, Moldova. Florentin Paladi is D.Sc., professor and former dean of the Faculty of Physics and Engineering and vice-rector for research at the Moldova State University (2012-2021). He earned a BSc diploma with distinction in Physics from Moldova State University in 1993, Ph.D. in Theoretical and Mathematical Physics in 1996, Doctor of Philosophy diploma in 1997, and D.Sc. in Physics and Mathematics in 2010. Laureate of the State Prize for outstanding young scientists in 1998. During the period of 1998-2002 he held a postdoctoral research position at the Tokyo Institute of Technology in Japan. In 2020 he founded the research laboratory Environmental Physics and Modeling Complex Systems. A Fulbright research scholar at the Centre for the Study of Complex Systems of the University of Michigan in Ann Arbor and research projects at the Brunel University in London and the University of Missouri in Columbia. He is Laureate of the Academy of Sciences of Moldova Award for the valuable scientific achievements of scientists in the natural and exact sciences for the development of analytical and numerical methods in complex systems research. Dr. Alexandr A. Barsuk, Moldova State University, Institute of Applied Physics, Chisinau, Moldova. Alexandr A. Barsuk is D.Sc., professor and principal scientific researcher in the research laboratory Environmental Physics and Modeling Complex Systems of the Institute of Applied Physics at the Moldova State University. Former head of the Computing Centre of the Moldova State University. D.Sc. in Physics and Mathematics from Tula State University in 1998. Research projects on analytical methods in structural mechanics and theoretical physics, variational and numerical analysis of stability of deformable bodies, and asymptotic analysis of complex systems. He is co-author of Stability of Axially Moving Materials (2020), part of the Springer Nature book series in Solid Mechanics and Its Applications. Prof. A.A. Barsuk is Laureate of the Ministry of Education and Research Award for his prodigious activity in the field of research and innovation. Dr. Orhan Özgür Aybar, Piri Reis University, Institute of Graduate Education - Computational Science and Engineering, Istanbul, Türkiye. Orhan Özgür Aybar is Ph.D., associate professor in the Department of Mathematics and Management Information Systems at Piri Reis University, where he has served since 2014 and was promoted to associate professor position in February 2024. He earned his Ph.D. in Mathematics from Gebze Institute of Technology in March 2014, following degrees in Physics with Computational Physics specialization from Bogazici University in Istanbul. Dr. Aybar’s research focuses on nonlinear dynamical systems, bifurcation theory, and stability analysis of differential equations and polynomial systems. His computational science contributions include developing algorithms for computer algebra systems to analyse biochemical reaction networks, implementing genetic algorithm approaches for chaotic system analysis, and creating symbolic computation methods for bifurcation detection in complex dynamical systems. Dr. Orhan Özgür Aybar serves as director of the Institute of Graduate Education and leads the Department of Computational Science and Engineering. Dr. Ilknur Kusbeyzi Aybar, Yeditepe University, Department of Mathematics, Istanbul, Türkiye. Ilknur Kusbeyzi Aybar is Ph.D., associate professor in the Department of Mathematics at Yeditepe University. She has been a faculty member at Yeditepe University since 2005, serving in various academic and administrative roles, and was promoted to associate professor position in February 2022. She earned her Ph.D. in Mathematics from Gebze Technical University in 2010, following undergraduate and master’s studies at Yıldız Technical University. Dr. Ilknur Kusbeyzi Aybar’s research focuses on the mathematical modeling and qualitative analysis of nonlinear dynamical systems, with particular emphasis on bifurcation and chaos theory, stability analysis, and symbolic computation in differential equations and polynomial systems. Her interdisciplinary interests extend to mathematical biology, neuronal dynamics, and chemical reaction modeling. Dr. Ilknur Kusbeyzi Aybar serves as head of the Department of Mathematics at Yeditepe University.

    Innehållsförteckning

    • 1. Introduction and Conceptual Foundations2. Bifurcation and Stability Analysis of Equilibrium States in Complex Thermodynamic Systems Near Equilibrium Parameter Values3. Sensitivity Analysis of Equilibrium States in Multi-Dimensional Dynamical Systems Near Ordinary and Bifurcation Parameter Values4. General Solution for Phase Transitions Involving an Intermediate Metastable State5. Unified Probabilistic Framework for Modeling Complex Adaptive Populations6. Neuronal Dynamics and Information Processing. From Single Neurons to Network Behavior7. Biochemical Reaction Networks. Mathematical Modeling of Cellular Processes8. Economic Motion in Mathematical Time. From Cycles to Chaos9. From Theory to Data. Empirical Methods for Economic Dynamical Systems10. Summary and Future Directions