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Author: Jim Duggan
Publisher: Springer
ISBN: 3319340433
Category : Computers
Languages : en
Pages : 188
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Book Description
This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author’s course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.
Author: Jim Duggan
Publisher: Springer
ISBN: 3319340433
Category : Computers
Languages : en
Pages : 188
Get Book Here
Book Description
This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author’s course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.
Author: Bruce Hannon
Publisher: Springer Science & Business Media
ISBN: 1468402242
Category : Computers
Languages : en
Pages : 247
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Book Description
Dynamic Modeling introduces an approach to modeling that makes it a more practical, intuitive endeavour. The book enables readers to convert their understanding of a phenomenon to a computer model, and then to run the model and let it yield the inevitable dynamic consequences built into the structure of the model. Part I provides an introduction to modeling dynamic systems, while Part II offers general methods for modeling. Parts III through to VIII then apply these methods to model real-world phenomena from chemistry, genetics, ecology, economics, and engineering. To develop and execute dynamic simulation models, Dynamic Modeling comes with STELLA II run- time software for Windows-based computers, as well as computer files of sample models used in the book. A clear, approachable introduction to the modeling process, of interest in any field where real problems can be illuminated by computer simulation.
Author: K.M. van Hee
Publisher: Elsevier
ISBN: 1483294846
Category : Computers
Languages : en
Pages : 368
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Book Description
The use of dynamic models in the development of information systems is regarded by many researchers as a promising issue in design support. Modelling the dynamics of information systems is likely to improve the quality and the performance of the design products. Dynamic modelling as a new approach for dynamic analysis of problems within an existing situation, and design and evaluation of different solution strategies may overcome many difficulties in the design process.
Author: Louis G. Birta
Publisher: Springer Science & Business Media
ISBN: 1846286212
Category : Computers
Languages : en
Pages : 463
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Book Description
This book provides a balanced and integrated presentation of modelling and simulation activity for both Discrete Event Dynamic Systems (DEDS) and Continuous Time Dynamic Systems (CYDS). The authors establish a clear distinction between the activity of modelling and that of simulation, maintaining this distinction throughout. The text offers a novel project-oriented approach for developing the modelling and simulation methodology, providing a solid basis for demonstrating the dependency of model structure and granularity on project goals. Comprehensive presentation of the verification and validation activities within the modelling and simulation context is also shown.
Author: Juš Kocijan
Publisher: Springer
ISBN: 3319210211
Category : Technology & Engineering
Languages : en
Pages : 281
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Book Description
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Author: Michael L. Deaton
Publisher: Springer Science & Business Media
ISBN: 1461213002
Category : Mathematics
Languages : en
Pages : 210
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Book Description
A primer on modeling concepts and applications that is specifically geared toward the environmental field. Sections on modeling terminology, the uses of models, the model-building process, and the interpretation of output provide the foundation for detailed applications. After an introduction to the basics of dynamic modeling, the book leads students through an analysis of several environmental problems, including surface-water pollution, matter-cycling disruptions, and global warming. The scientific and technical context is provided for each problem, and the methods for analyzing and designing appropriate modeling approaches is provided. While the mathematical content does not exceed the level of a first-semester calculus course, the book gives students all of the background, examples, and practice exercises needed both to use and understand environmental modeling. It is suitable for upper-level undergraduate and beginning-graduate level environmental professionals seeking an introduction to modeling in their field.
Author: Robert L. Woods
Publisher: Pearson
ISBN:
Category : Mathematics
Languages : en
Pages : 552
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Book Description
Introduction to modeling and simulation - Models for dynamic systems and systems similarity - Modeling of engineering systems - Mechanical systems - Electrical systems - Fluid systems - Thermal systems - Mixed discipline systems - System dynamic response analysis - Frequency response - Time response and digital simulation - Engineering applications - System design and selection of components.
Author: Hazhir Rahmandad
Publisher: MIT Press
ISBN: 0262331438
Category : Business & Economics
Languages : en
Pages : 443
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Book Description
A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel
Author: Lennart Ljung
Publisher: Prentice Hall
ISBN: 9780135970973
Category : Computer simulation
Languages : en
Pages : 0
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Book Description
Written by a recognized authority in the field of identification and control, this book draws together into a single volume the important aspects of system identification AND physical modelling. KEY TOPICS: Explores techniques used to construct mathematical models of systems based on knowledge from physics, chemistry, biology, etc. (e.g., techniques with so called bond-graphs, as well those which use computer algebra for the modeling work). Explains system identification techniques used to infer knowledge about the behavior of dynamic systems based on observations of the various input and output signals that are available for measurement. Shows how both types of techniques need to be applied in any given practical modeling situation. Considers applications, primarily simulation. MARKET: For practicing engineers who are faced with problems of modeling.
Author: Matthias Ruth
Publisher: Springer Science & Business Media
ISBN: 1461422086
Category : Business & Economics
Languages : en
Pages : 324
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Book Description
This book explores the dynamic processes in economic systems, concentrating on the extraction and use of the natural resources required to meet economic needs. Sections cover methods for dynamic modeling in economics, microeconomic models of firms, modeling optimal use of both nonrenewable and renewable resources, and chaos in economic models. This book does not require a substantial background in mathematics or computer science.
