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Large Scale Computing Techniques For Complex System Simulations
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Book Synopsis Large-Scale Computing Techniques for Complex System Simulations by : Werner Dubitzky
Download or read book Large-Scale Computing Techniques for Complex System Simulations written by Werner Dubitzky and published by John Wiley & Sons. This book was released on 2012-02-03 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and to provide a communications platform facilitating an exchange of concepts, ideas and needs between the scientists and technologist and complex system modelers. On the application side, the book focuses on modeling and simulation of natural and man-made complex systems. On the computing technology side, emphasis is placed on the distributed computing approaches, but supercomputing and other novel technologies are also considered.
Book Synopsis Large-Scale Computing Techniques for Complex System Simulations by : Werner Dubitzky
Download or read book Large-Scale Computing Techniques for Complex System Simulations written by Werner Dubitzky and published by Wiley-IEEE Computer Society Press. This book was released on 2012-04-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and to provide a communications platform facilitating an exchange of concepts, ideas and needs between the scientists and technologist and complex system modelers. On the application side, the book focuses on modeling and simulation of natural and man-made complex systems. On the computing technology side, emphasis is placed on the distributed computing approaches, but supercomputing and other novel technologies are also considered.
Book Synopsis Co-evolution of Intelligent Socio-technical Systems by : Evangelia Mitleton-Kelly
Download or read book Co-evolution of Intelligent Socio-technical Systems written by Evangelia Mitleton-Kelly and published by Springer. This book was released on 2013-05-27 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the interconnectivity between humans through technical devices is becoming ubiquitous, the next step is already in the making: ambient intelligence, i.e. smart (technical) environments, which will eventually play the same active role in communication as the human players, leading to a co-evolution in all domains where real-time communication is essential. This topical volume, based on the findings of the Socionical European research project, gives equal attention to two highly relevant domains of applications: transport, specifically traffic, dynamics from the viewpoint of a socio-technical interaction and evacuation scenarios for large-scale emergency situations. Care was taken to investigate as much as possible the limits of scalability and to combine the modeling using complex systems science approaches with relevant data analysis.
Book Synopsis Agent-based Modeling and Simulation in Archaeology by : Gabriel Wurzer
Download or read book Agent-based Modeling and Simulation in Archaeology written by Gabriel Wurzer and published by Springer. This book was released on 2014-11-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Archaeology has been historically reluctant to embrace the subject of agent-based simulation, since it was seen as being used to "re-enact" and "visualize" possible scenarios for a wider (generally non-scientific) audience, based on scarce and fuzzy data. Furthermore, modeling "in exact terms" and programming as a means for producing agent-based simulations were simply beyond the field of the social sciences. This situation has changed quite drastically with the advent of the internet age: Data, it seems, is now ubiquitous. Researchers have switched from simply collecting data to filtering, selecting and deriving insights in a cybernetic manner. Agent-based simulation is one of the tools used to glean information from highly complex excavation sites according to formalized models, capturing essential properties in a highly abstract and yet spatial manner. As such, the goal of this book is to present an overview of techniques used and work conducted in that field, drawing on the experience of practitioners.
Book Synopsis Social Simulation for a Digital Society by : Diane Payne
Download or read book Social Simulation for a Digital Society written by Diane Payne and published by Springer Nature. This book was released on 2019-11-18 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Social Simulation for a Digital Society” provides a cross-section of state-of-the-art research in social simulation and computational social science. With the availability of big data and faster computing power, the social sciences are undergoing a tremendous transformation. Research in computational social sciences has received considerable attention in the last few years, with advances in a wide range of methodologies and applications. Areas of application of computational methods range from the study of opinion and information dynamics in social networks, the formal modeling of resource use, the study of social conflict and cooperation to the development of cognitive models for social simulation and many more. This volume is based on the Social Simulation Conference of 2017 in Dublin and includes applications from across the social sciences, providing the reader with a demonstration of the highly versatile research in social simulation, with a particular focus on public policy relevance in a digital society. Chapters in the book include contributions to the methodology of simulation-based research, theoretical and philosophical considerations, as well as applied work. This book will appeal to students and researchers in the field.
Book Synopsis Understanding Complex Urban Systems by : Christian Walloth
Download or read book Understanding Complex Urban Systems written by Christian Walloth and published by Springer. This book was released on 2016-03-11 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the modeling and understanding of complex urban systems. This second volume of Understanding Complex Urban Systems focuses on the challenges of the modeling tools, concerning, e.g., the quality and quantity of data and the selection of an appropriate modeling approach. It is meant to support urban decision-makers—including municipal politicians, spatial planners, and citizen groups—in choosing an appropriate modeling approach for their particular modeling requirements. The contributors to this volume are from different disciplines, but all share the same goal: optimizing the representation of complex urban systems. They present and discuss a variety of approaches for dealing with data-availability problems and finding appropriate modeling approaches—and not only in terms of computer modeling. The selection of articles featured in this volume reflect a broad variety of new and established modeling approaches such as: - An argument for using Big Data methods in conjunction with Agent-based Modeling; - The introduction of a participatory approach involving citizens, in order to utilize an Agent-based Modeling approach to simulate urban-growth scenarios; - A presentation of semantic modeling to enable a flexible application of modeling methods and a flexible exchange of data; - An article about a nested-systems approach to analyzing a city’s interdependent subsystems (according to these subsystems’ different velocities of change); - An article about methods that use Luhmann’s system theory to characterize cities as systems that are composed of flows; - An article that demonstrates how the Sen-Nussbaum Capabilities Approach can be used in urban systems to measure household well-being shifts that occur in response to the resettlement of urban households; - A final article that illustrates how Adaptive Cycles of Complex Adaptive Systems, as well as innovation, can be applied to gain a better understanding of cities and to promote more resilient and more sustainable urban futures.
Book Synopsis Modeling and Simulation in HPC and Cloud Systems by : Joanna Kołodziej
Download or read book Modeling and Simulation in HPC and Cloud Systems written by Joanna Kołodziej and published by Springer. This book was released on 2018-01-30 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners.
Book Synopsis Modeling Multi-Level Systems by : Octavian Iordache
Download or read book Modeling Multi-Level Systems written by Octavian Iordache and published by Springer Science & Business Media. This book was released on 2011-02-07 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale systems. Taking inspiration from systems sciences, chapters 9 to 11 highlight multi-level modeling potentialities in formal concept analysis, existential graphs and evolvable designs of experiments. Case studies refer to separation flow-sheets, pharmaceutical pipeline, drug design and development, reliability management systems, security and failure analysis. Perspectives and integrative points of view are discussed in chapter 12. Autonomous and viable systems, multi-agents, organic and autonomic computing, multi-level informational systems, are revealed as promising domains for future applications. Written for: engineers, researchers, entrepreneurs and students in chemical, pharmaceutical, environmental and systems sciences engineering, and for applied mathematicians.
Book Synopsis Complex Systems in Knowledge-based Environments: Theory, Models and Applications by : Andreas Tolk
Download or read book Complex Systems in Knowledge-based Environments: Theory, Models and Applications written by Andreas Tolk and published by Springer Science & Business Media. This book was released on 2009-01-17 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tremendous growth in the availability of inexpensive computing power and easy availability of computers have generated tremendous interest in the design and imp- mentation of Complex Systems. Computer-based solutions offer great support in the design of Complex Systems. Furthermore, Complex Systems are becoming incre- ingly complex themselves. This research book comprises a selection of state-of-the-art contributions to topics dealing with Complex Systems in a Knowledge-based En- ronment. Complex systems are ubiquitous. Examples comprise, but are not limited to System of Systems, Service-oriented Approaches, Agent-based Systems, and Complex Distributed Virtual Systems. These are application domains that require knowledge of engineering and management methods and are beyond the scope of traditional systems. The chapters in this book deal with a selection of topics which range from unc- tainty representation, management and the use of ontological means which support and are large-scale business integration. All contributions were invited and are based on the recognition of the expertise of the contributing authors in the field. By colle- ing these sources together in one volume, the intention was to present a variety of tools to the reader to assist in both study and work. The second intention was to show how the different facets presented in the chapters are complementary and contribute towards this emerging discipline designed to aid in the analysis of complex systems.
Book Synopsis High-performance Computing Methods in Large-scale Power System Simulation by : Lukas Razik
Download or read book High-performance Computing Methods in Large-scale Power System Simulation written by Lukas Razik and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis High-Performance Modelling and Simulation for Big Data Applications by : Joanna Kołodziej
Download or read book High-Performance Modelling and Simulation for Big Data Applications written by Joanna Kołodziej and published by Springer. This book was released on 2019-03-25 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
Book Synopsis Simulating Complex Systems by Cellular Automata by : Alfons G. Hoekstra
Download or read book Simulating Complex Systems by Cellular Automata written by Alfons G. Hoekstra and published by Springer. This book was released on 2010-06-03 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on theory and applications, and a smaller part on software. The theory part contains fundamental chapters on how to design and/or apply CA for many different areas. In the applications part a number of representative examples of really using CA in a broad range of disciplines is provided - this part will give the reader a good idea of the real strength of this kind of modeling as well as the incentive to apply CA in their own field of study. Finally, we included a smaller section on software, to highlight the important work that has been done to create high quality problem solving environments that allow to quickly and relatively easily implement a CA model and run simulations, both on the desktop and if needed, on High Performance Computing infrastructures.
Book Synopsis Strategic Engineering for Cloud Computing and Big Data Analytics by : Amin Hosseinian-Far
Download or read book Strategic Engineering for Cloud Computing and Big Data Analytics written by Amin Hosseinian-Far and published by Springer. This book was released on 2017-02-13 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the use of a wide range of strategic engineering concepts, theories and applied case studies to improve the safety, security and sustainability of complex and large-scale engineering and computer systems. It first details the concepts of system design, life cycle, impact assessment and security to show how these ideas can be brought to bear on the modeling, analysis and design of information systems with a focused view on cloud-computing systems and big data analytics. This informative book is a valuable resource for graduate students, researchers and industry-based practitioners working in engineering, information and business systems as well as strategy.
Book Synopsis Big Data in Complex Systems by : Aboul Ella Hassanien
Download or read book Big Data in Complex Systems written by Aboul Ella Hassanien and published by Springer. This book was released on 2015-01-02 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.
Book Synopsis Modeling Large-scale Computing Systems by : Paweł Czarnul
Download or read book Modeling Large-scale Computing Systems written by Paweł Czarnul and published by . This book was released on 2016 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Intelligent Modelling and Simulation by : Joanna Kołodziej
Download or read book Advances in Intelligent Modelling and Simulation written by Joanna Kołodziej and published by Springer. This book was released on 2012-07-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under various types of users with evolving relationships fraught with uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics.
Book Synopsis Model Management and Analytics for Large Scale Systems by : Bedir Tekinerdogan
Download or read book Model Management and Analytics for Large Scale Systems written by Bedir Tekinerdogan and published by Academic Press. This book was released on 2019-09-14 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
