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Modeling Complex Systems
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Book Synopsis Modeling Complex Systems by : Nino Boccara
Download or read book Modeling Complex Systems written by Nino Boccara and published by Springer Science & Business Media. This book was released on 2010-09-09 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates how models of complex systems are built up and provides indispensable mathematical tools for studying their dynamics. This second edition includes more recent research results and many new and improved worked out examples and exercises.
Book Synopsis Modeling of Complex Systems by : V. Vemuri
Download or read book Modeling of Complex Systems written by V. Vemuri and published by Academic Press. This book was released on 2014-05-10 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Complex Systems: An Introduction describes the framework of complex systems. This book discusses the language of system theory, taxonomy of system concepts, steps in model building, and establishing relations using physical laws. The statistical attributes of data, generation of random numbers fundamental problems of recognition, and input-output type models are also elaborated. This text likewise covers the optimization with equality constraints, transfer function models, and competition among species. This publication is written primarily for senior undergraduate students and beginning graduate students who are interested in an interdisciplinary or multidisciplinary approach to large-scale or complex problems of contemporary societal interest.
Book Synopsis Modeling Complex Living Systems by : N. Bellomo
Download or read book Modeling Complex Living Systems written by N. Bellomo and published by Springer Science & Business Media. This book was released on 2008 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops different mathematical methods and tools to model living systems. This book presents material that can be used in such real-world applications as immunology, transportation engineering, and economics. It is of interest to those involved in modeling complex social systems and living matter in general.
Book Synopsis Complex Systems and Self-organization Modelling by : Cyrille Bertelle
Download or read book Complex Systems and Self-organization Modelling written by Cyrille Bertelle and published by Springer Science & Business Media. This book was released on 2008-12-03 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, the outcome of a workshop meeting within ESM 2006, explores the use of emergent computing and self-organization modeling within various applications of complex systems.
Book Synopsis Smart Modeling and Simulation for Complex Systems by : Quan Bai
Download or read book Smart Modeling and Simulation for Complex Systems written by Quan Bai and published by Springer. This book was released on 2015-01-10 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.
Book Synopsis Simulation of Complex Systems by : Aykut Argun
Download or read book Simulation of Complex Systems written by Aykut Argun and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the most fundamental and essential techniques to simulate complex systems, from the dynamics of molecules to the spreading of diseases, from optimization using ant colonies to the simulation of the Game of Life.
Book Synopsis Modeling and Control of Complex Systems by : Petros A. Ioannou
Download or read book Modeling and Control of Complex Systems written by Petros A. Ioannou and published by CRC Press. This book was released on 2007-12-26 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand pos
Book Synopsis Modeling and Simulation of Complex Systems by : Robert Siegfried
Download or read book Modeling and Simulation of Complex Systems written by Robert Siegfried and published by Springer Vieweg. This book was released on 2014-10-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models –from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.
Book Synopsis Modeling Cities and Regions as Complex Systems by : Roger White
Download or read book Modeling Cities and Regions as Complex Systems written by Roger White and published by MIT Press. This book was released on 2015-09-11 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory and practice of modeling cities and regions as complex, self-organizing systems, presenting widely used cellular automata-based models, theoretical discussions, and applications. Cities and regions grow (or occasionally decline), and continuously transform themselves as they do so. This book describes the theory and practice of modeling the spatial dynamics of urban growth and transformation. As cities are complex, adaptive, self-organizing systems, the most appropriate modeling framework is one based on the theory of self-organizing systems—an approach already used in such fields as physics and ecology. The book presents a series of models, most of them developed using cellular automata (CA), which are inherently spatial and computationally efficient. It also provides discussions of the theoretical, methodological, and philosophical issues that arise from the models. A case study illustrates the use of these models in urban and regional planning. Finally, the book presents a new, dynamic theory of urban spatial structure that emerges from the models and their applications. The models are primarily land use models, but the more advanced ones also show the dynamics of population and economic activities, and are integrated with models in other domains such as economics, demography, and transportation. The result is a rich and realistic representation of the spatial dynamics of a variety of urban phenomena. The book is unique in its coverage of both the general issues associated with complex self-organizing systems and the specifics of designing and implementing models of such systems.
Book Synopsis Complex Systems Modeling and Simulation in Economics and Finance by : Shu-Heng Chen
Download or read book Complex Systems Modeling and Simulation in Economics and Finance written by Shu-Heng Chen and published by Springer. This book was released on 2018-11-20 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This title brings together frontier research on complex economic systems, heterogeneous interacting agents, bounded rationality, and nonlinear dynamics in economics. The book contains the proceedings of the CEF2015 (21st Computing in Economics in Finance), held 20-22 June 2015 in Taipei, Taiwan, and addresses some of the important driving forces for various emergent properties in economies, when viewed as complex systems. The breakthroughs reported in this book are a result of an interdisciplinary approach and simulation remains the unifying theme for these papers as they deal with a wide range of topics in economics. The text is a valuable addition to the efforts in promoting the complex systems view in economic science. The computational experiments reported in the book are both transparent and replicable. Complex System Modeling and Simulation in Economics and Finance is useful for graduate courses of complex systems, with particular focus on economics and finance. At the same time it serves as a good overview for researchers who are interested in the topic.
Book Synopsis Social-Behavioral Modeling for Complex Systems by : Paul K. Davis
Download or read book Social-Behavioral Modeling for Complex Systems written by Paul K. Davis and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations. With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology. In brief, the volume discusses: Cutting-edge challenges and opportunities in modeling for social and behavioral science Special requirements for achieving high standards of privacy and ethics New approaches for developing theory while exploiting both empirical and computational data Issues of reproducibility, communication, explanation, and validation Special requirements for models intended to inform decision making about complex social systems
Book Synopsis Dynamic Mode Decomposition by : J. Nathan Kutz
Download or read book Dynamic Mode Decomposition written by J. Nathan Kutz and published by SIAM. This book was released on 2016-11-23 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Book Synopsis Emergent Behavior in Complex Systems Engineering by : Saurabh Mittal
Download or read book Emergent Behavior in Complex Systems Engineering written by Saurabh Mittal and published by John Wiley & Sons. This book was released on 2018-04-17 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive text that reviews the methods and technologies that explore emergent behavior in complex systems engineering in multidisciplinary fields In Emergent Behavior in Complex Systems Engineering, the authors present the theoretical considerations and the tools required to enable the study of emergent behaviors in manmade systems. Information Technology is key to today’s modern world. Scientific theories introduced in the last five decades can now be realized with the latest computational infrastructure. Modeling and simulation, along with Big Data technologies are at the forefront of such exploration and investigation. The text offers a number of simulation-based methods, technologies, and approaches that are designed to encourage the reader to incorporate simulation technologies to further their understanding of emergent behavior in complex systems. The authors present a resource for those designing, developing, managing, operating, and maintaining systems, including system of systems. The guide is designed to help better detect, analyse, understand, and manage the emergent behaviour inherent in complex systems engineering in order to reap the benefits of innovations and avoid the dangers of unforeseen consequences. This vital resource: Presents coverage of a wide range of simulation technologies Explores the subject of emergence through the lens of Modeling and Simulation (M&S) Offers contributions from authors at the forefront of various related disciplines such as philosophy, science, engineering, sociology, and economics Contains information on the next generation of complex systems engineering Written for researchers, lecturers, and students, Emergent Behavior in Complex Systems Engineering provides an overview of the current discussions on complexity and emergence, and shows how systems engineering methods in general and simulation methods in particular can help in gaining new insights in complex systems engineering.
Book Synopsis Qualitative Modeling of Complex Systems by : Charles J. Puccia
Download or read book Qualitative Modeling of Complex Systems written by Charles J. Puccia and published by . This book was released on 1985 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this modern era of mathematical modeling, applications have become increasingly complicated. As the complexity grows, it becomes more and more difficult to draw meaningful conclusions about the behavior of theoretical models and their relations to reality. Alongside methods that emphasize quantitative properties and the testing of scientific details, there is a need for approaches that are more qualitative. These techniques attempt to cover whole families of models in one bold stroke, in a manner that allows robust conclusions to be drawn about them. Loop analysis and time averaging provide a means of interpreting the properties of systems from the network of interactions within the system. The authors' methodology concentrates on graphical representation to guide experimental design, to identify sources of external variability from the statistical pattern of variables, and to make management decisions. Although most of the examples are drawn from ecology, the methods are relevant to all of the pure and applied sciences. This relevance is enhanced by case studies from such diverse areas as physiology, resource management, the behavioral sciences, and social epidemiology. The book will be useful to a broad readership from the biological and social sciences as well as the physical sciences and technology. It will interest undergraduate and graduate students along with researchers active in these disciplines. Here the reader will find a strong rationale for maintaining a holistic approach, revealing what insights and advantages are retained by the broader perspective and, more explicitly, by the synergistic effects that cannot be discerned by reducing systems to their smallest parts.
Book Synopsis An Introduction to Agent-Based Modeling by : Uri Wilensky
Download or read book An Introduction to Agent-Based Modeling written by Uri Wilensky and published by MIT Press. This book was released on 2015-04-03 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
Book Synopsis Complex Systems in the Social and Behavioral Sciences by : L. Douglas Kiel
Download or read book Complex Systems in the Social and Behavioral Sciences written by L. Douglas Kiel and published by . This book was released on 2021-06-22 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complexity systems are at the heart of behavior
Book Synopsis Predictive Approaches to Control of Complex Systems by : Gorazd Karer
Download or read book Predictive Approaches to Control of Complex Systems written by Gorazd Karer and published by Springer. This book was released on 2012-09-20 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequently encountered complex dynamical phenomena and are practically applicable in the proposed predictive control approaches. Furthermore, unsupervised learning methods that can be used for complex-system identification are treated. Finally, several useful predictive control algorithms for complex systems are proposed and their particular advantages and drawbacks are discussed. The presented modeling, identification and control approaches are complemented by illustrative examples. The book is aimed towards researches and postgraduate students interested in modeling, identification and control, as well as towards control engineers needing practically usable advanced control methods for complex systems.
