System Dynamics

Modelling and Simulation

Author: Bilash Kanti Bala,Fatimah Mohamed Arshad,Kusairi Mohd Noh

Publisher: Springer

ISBN: 9811020450

Category: Business & Economics

Page: 278

View: 3841

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This book covers the broad spectrum of system dynamics methodologies for the modelling and simulation of complex systems: systems thinking, causal diagrams, systems structure of stock and flow diagrams, parameter estimation and tests for confidence building in system dynamics models. It includes a comprehensive review of model validation and policy design and provides a practical presentation of system dynamics modelling. It also offers numerous worked-out examples and case studies in diverse fields using STELLA and VENSIM. The system dynamics methodologies presented here can be applied to nearly all areas of research and planning, and the simulations provided make the complicated issues more easily understandable. System Dynamics: Modelling and Simulation is an essential system dynamics and systems engineering textbook for undergraduate and graduate courses. It also offers an excellent reference guide for managers in industry and policy planners who wish to use modelling and simulation to manage complex systems more effectively, as well as researchers in the fields of modelling and simulation-based systems thinking.

Modeling and simulation of dynamic systems

Author: Robert L. Woods,Kent L. Lawrence

Publisher: N.A

ISBN: 9780133373790

Category: Mathematics

Page: 521

View: 8933

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This book reflects the state-of-the-art and current trends in modeling and simulation. The book provides comprehensive coverage of 1) the modeling techniques of the major types of dynamic engineering systems, 2) the solution techniques for the resulting differential equations for linear and nonlinear systems, and 3) the attendant mathematical procedures related to the presentation of dynamic systems and determination of their time and frequency response characteristics. It explains in detail how to select all of the system component parameter values for static and dynamic performance specifications and limits. For anyone interested in systems dynamics, modeling, and interdisciplinary systems.

System Dynamics Modeling with R

Author: Jim Duggan

Publisher: Springer

ISBN: 3319340433

Category: Computers

Page: 176

View: 2161

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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.

Practical Exercises of System Dynamics

System Dynamics. Simulation and models with Vensim PLE. Preface John Sterman

Author: Juan Martín García

Publisher: Juan Martín García

ISBN: 8460998045

Category: Biological systems

Page: 282

View: 5541

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This book is a guide that shows step by step the process of building simulation models using System Dynamics. It is written in a clear and comprehensible style that illustrates the model construction process. This book will be a useful resource to students, scholars, researchers, and teachers.

Guide to Modeling and Simulation of Systems of Systems

Author: Bernard P. Zeigler,Hessam S. Sarjoughian

Publisher: Springer

ISBN: 3319641344

Category: Computers

Page: 400

View: 3089

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This easy-to-follow textbook provides an exercise-driven guide to the use of the Discrete Event Systems Specification (DEVS) simulation modeling formalism and the System Entity Structure (SES) simulation model ontology supported with the latest advances in software architecture and design principles, methods, and tools for building and testing virtual Systems of Systems (SoS). The book examines a wide variety of SoS problems, ranging from cloud computing systems to biological systems in agricultural food crops. This enhanced and expanded second edition also features a new chapter on DEVS support for Markov modeling and simulation. Topics and features: provides an extensive set of exercises throughout the text to reinforce the concepts and encourage use of the tools, supported by introduction and summary sections; discusses how the SoS concept and supporting virtual build and test environments can overcome the limitations of current approaches; offers a step-by-step introduction to the DEVS concepts and modeling environment features required to build sophisticated SoS models; describes the capabilities and use of the tools CoSMoS/DEVS-Suite, Virtual Laboratory Environment, and MS4 MeTM; reviews a range of diverse applications, from the development of new satellite design and launch technologies, to surveillance and control in animal epidemiology; examines software/hardware co-design for SoS, and activity concepts that bridge information-level requirements and energy consumption in the implementation; demonstrates how the DEVS formalism supports Markov modeling within an advanced modeling and simulation environment (NEW). This accessible and hands-on textbook/reference provides invaluable practical guidance for graduate students interested in simulation software development and cyber-systems engineering design, as well as for practitioners in these, and related areas.

Complex Systems Modeling and Simulation in Economics and Finance

Author: Shu-Heng Chen,Ying-Fang Kao,Ragupathy Venkatachalam,Ye-Rong Du

Publisher: Springer

ISBN: 9783319996226

Category: Business & Economics

Page: 390

View: 1769

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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.

Analytical System Dynamics

Modeling and Simulation

Author: Brian Fabien

Publisher: Springer Science & Business Media

ISBN: 0387856056

Category: Technology & Engineering

Page: 326

View: 8364

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"Analytical System Dynamics: Modeling and Simulation" combines results from analytical mechanics and system dynamics to develop an approach to modeling constrained multidiscipline dynamic systems. This combination yields a modeling technique based on the energy method of Lagrange, which in turn, results in a set of differential-algebraic equations that are suitable for numerical integration. Using the modeling approach presented in this book enables one to model and simulate systems as diverse as a six-link, closed-loop mechanism or a transistor power amplifier.

Introduction to Process Control

Analysis, Mathematical Modeling, Control and Optimization

Author: Victor A. Skormin

Publisher: Springer

ISBN: 3319422588

Category: Business & Economics

Page: 254

View: 9206

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This textbook is intended for an introductory graduate level on process control, taught in most engineering curricula. It focuses on the statistical techniques and methods of control and system optimization needed for the mathematical modeling, analysis, simulation, control and optimization of multivariable manufacturing processes. In four sections, it covers: Relevant mathematical methods, including random events, variables and processes, and their characteristics; estimation and confidence intervals; Bayes applications; correlation and regression analysis; statistical cluster analysis; and singular value decomposition for classification applications. Mathematical description of manufacturing processes, including static and dynamic models; model validation; confidence intervals for model parameters; principal component analysis; conventional and recursive least squares procedures; nonlinear least squares; and continuous-time, discrete-time, s-domain and Z-domain models. Control of manufacturing processes, including transfer function/transfer matrix models; state-variable models; methods of discrete-time classical control; state variable discrete-time control; state observers/estimators in control systems; methods of decoupling control; and methods of adaptive control. Methods and applications of system optimization, including unconstrained and constrained optimization; analytical and numerical optimization procedures; use of penalty functions; methods of linear programming; gradient methods; direct search methods; genetic optimization; methods and applications of dynamic programming; and applications to estimation, design, control, and planning. Each section of the book will include end-of-chapter exercises, and the book will be suitable for any systems, electrical, chemical, or industrial engineering program, as it focuses on the processes themselves, and not on the product being manufactured. Students will be able to obtain a mathematical model of any manufacturing process, to design a computer-based control system for a particular continuous manufacturing process, and be able to formulate an engineering problem in terms of optimization, as well as the ability to choose and apply the appropriate optimization technique.

Supply Chain Simulation

A System Dynamics Approach for Improving Performance

Author: Francisco Campuzano,Josefa Mula

Publisher: Springer Science & Business Media

ISBN: 9780857297198

Category: Technology & Engineering

Page: 106

View: 1238

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Supply Chain Simulation allows readers to practice modeling and simulating a multi-level supply chain. The chapters are a combination of the practical and the theoretical, covering: knowledge of simulation methods and techniques, the conceptual framework of a typical supply chain, the main concepts of system dynamics, and a set of practice problems with their corresponding solutions. The problem set includes illustrations and graphs relating to the simulation results of the Vensim® program, the main code of which is also provided. The examples used are a valuable simulation tool that can be modified and extended according to user requirements. The objective of Supply Chain Simulation is to meet the demands of supply chain simulation or similar courses taught at the postgraduate level. The “what if” analysis recreates different simulation scenarios to improve the decision-making process in terms of supply chain performance, making the book useful not only for postgraduate students, but also for industrial practitioners.

Modeling and Simulation

An Application-Oriented Introduction

Author: Hans-Joachim Bungartz,Stefan Zimmer,Martin Buchholz,Dirk Pflüger

Publisher: Springer Science & Business Media

ISBN: 3642395244

Category: Computers

Page: 413

View: 2656

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Die Autoren führen auf anschauliche und systematische Weise in die mathematische und informatische Modellierung sowie in die Simulation als universelle Methodik ein. Es geht um Klassen von Modellen und um die Vielfalt an Beschreibungsarten. Aber es geht immer auch darum, wie aus Modellen konkrete Simulationsergebnisse gewonnen werden können. Nach einem kompakten Repetitorium zum benötigten mathematischen Apparat wird das Konzept anhand von Szenarien u. a. aus den Bereichen „Spielen – entscheiden – planen" und „Physik im Rechner" umgesetzt.

Measurements, Modelling and Simulation of Dynamic Systems

Author: Edward Layer,Krzysztof Tomczyk

Publisher: Springer Science & Business Media

ISBN: 9783642045882

Category: Mathematics

Page: 156

View: 3936

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The development and use of models of various objects is becoming a more common practice in recent days. This is due to the ease with which models can be developed and examined through the use of computers and appropriate software. Of those two, the former - high-speed computers - are easily accessible nowadays, and the latter - existing programs - are being updated almost continuously, and at the same time new powerful software is being developed. Usually a model represents correlations between some processes and their interactions, with better or worse quality of representation. It details and characterizes a part of the real world taking into account a structure of phenomena, as well as quantitative and qualitative relations. There are a great variety of models. Modelling is carried out in many diverse fields. All types of natural phenomena in the area of biology, ecology and medicine are possible subjects for modelling. Models stand for and represent technical objects in physics, chemistry, engineering, social events and behaviours in sociology, financial matters, investments and stock markets in economy, strategy and tactics, defence, security and safety in military fields. There is one common point for all models. We expect them to fulfil the validity of prediction. It means that through the analysis of models it is possible to predict phenomena, which may occur in a fragment of the real world represented by a given model. We also expect to be able to predict future reactions to signals from the outside world.

Mathematical Modeling in Economics, Ecology and the Environment

Author: Natali Hritonenko,Yuri Yatsenko

Publisher: Springer Science & Business Media

ISBN: 1461493110

Category: Mathematics

Page: 296

View: 5725

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Updated to textbook form by popular demand, this second edition discusses diverse mathematical models used in economics, ecology, and the environmental sciences with emphasis on control and optimization. It is intended for graduate and upper-undergraduate course use, however, applied mathematicians, industry practitioners, and a vast number of interdisciplinary academics will find the presentation highly useful. Core topics of this text are: · Economic growth and technological development · Population dynamics and human impact on the environment · Resource extraction and scarcity · Air and water contamination · Rational management of the economy and environment · Climate change and global dynamics The step-by-step approach taken is problem-based and easy to follow. The authors aptly demonstrate that the same models may be used to describe different economic and environmental processes and that similar investigation techniques are applicable to analyze various models. Instructors will appreciate the substantial flexibility that this text allows while designing their own syllabus. Chapters are essentially self-contained and may be covered in full, in part, and in any order. Appropriate one- and two-semester courses include, but are not limited to, Applied Mathematical Modeling, Mathematical Methods in Economics and Environment, Models of Biological Systems, Applied Optimization Models, and Environmental Models. Prerequisites for the courses are Calculus and, preferably, Differential Equations.

Mathematical Modeling of Collective Behavior in Socio-Economic and Life Sciences

Author: Giovanni Naldi,Lorenzo Pareschi,Giuseppe Toscani

Publisher: Springer Science & Business Media

ISBN: 0817649468

Category: Mathematics

Page: 438

View: 3098

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Using examples from finance and modern warfare to the flocking of birds and the swarming of bacteria, the collected research in this volume demonstrates the common methodological approaches and tools for modeling and simulating collective behavior. The topics presented point toward new and challenging frontiers of applied mathematics, making the volume a useful reference text for applied mathematicians, physicists, biologists, and economists involved in the modeling of socio-economic systems.

Nonlinear Dynamics in Economics, Finance and the Social Sciences

Essays in Honour of John Barkley Rosser Jr

Author: Gian Italo Bischi,Carl Chiarella,Laura Gardini

Publisher: Springer Science & Business Media

ISBN: 9783642040238

Category: Business & Economics

Page: 384

View: 4204

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Over the last two decades there has been a great deal of research into nonlinear dynamic models in economics, finance and the social sciences. This book contains twenty papers that range over very recent applications in these areas. Topics covered include structural change and economic growth, disequilibrium dynamics and economic policy as well as models with boundedly rational agents. The book illustrates some of the most recent research tools in this area and will be of interest to economists working in economic dynamics and to mathematicians interested in seeing ideas from nonlinear dynamics and complexity theory applied to the economic sciences.

Simulation and Inference for Stochastic Differential Equations

With R Examples

Author: Stefano M. Iacus

Publisher: Springer Science & Business Media

ISBN: 9780387758398

Category: Computers

Page: 286

View: 2524

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This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too.

Dynamics and Control of Switched Electronic Systems

Advanced Perspectives for Modeling, Simulation and Control of Power Converters

Author: Francesco Vasca,Luigi Iannelli

Publisher: Springer Science & Business Media

ISBN: 1447128850

Category: Technology & Engineering

Page: 494

View: 7411

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The increased efficiency and quality constraints imposed on electrical energy systems have inspired a renewed research interest in the study of formal approaches to the analysis and control of power electronics converters. Switched systems represent a useful framework for modeling these converters and the peculiarities of their operating conditions and control goals justify the specific classification of “switched electronic systems”. Indeed, idealized switched models of power converters introduce problems not commonly encountered when analyzing generic switched models or non-switched electrical networks. In that sense the analysis of switched electronic systems represents a source for new ideas and benchmarks for switched and hybrid systems generally. Dynamics and Control of Switched Electronic Systems draws on the expertise of an international group of expert contributors to give an overview of recent advances in the modeling, simulation and control of switched electronic systems. The reader is provided with a well-organized source of references and a mathematically-based report of the state of the art in analysis and design techniques for switched power converters. Intuitive language, realistic illustrative examples and numerical simulations help the reader to come to grips with the rigorous presentation of many promising directions of research such as: converter topologies and modulation techniques; continuous-time, discrete-time and hybrid models; modern control strategies for power converters; and challenges in numerical simulation. The guidance and information imparted in this text will be appreciated by engineers, and applied mathematicians working on system and circuit theory, control systems development, and electronic and energy conversion systems design.

Analytical Methods for Dynamic Modelers

Author: Hazhir Rahmandad,Rogelio Oliva,Nathaniel D. Osgood,George Richardson

Publisher: MIT Press

ISBN: 0262331438

Category: Business & Economics

Page: 448

View: 6811

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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.ContributorsWenyi 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

Modelling and Simulation

Exploring Dynamic System Behaviour

Author: Louis G. Birta,Gilbert Arbez

Publisher: Springer Science & Business Media

ISBN: 1447127838

Category: Computers

Page: 437

View: 2283

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This textbook presents a practical introduction to the fundamental aspects of modelling and simulation. It provides the necessary foundations both for those wishing to learn about this methodology and also for those who have a need to apply it in their work. Illustrative examples are drawn from projects formulated within the domains of both DEDS and CTDS. Features: presents a project-oriented perspective; describes an activity-based conceptual modelling framework (ABCmod) for DEDS; includes a new chapter that presents a novel world view, the Activity-Object world view, which eases the translation of a conceptual model specification in the ABCmod framework into a simulation program; contains numerous illustrative examples, useful algorithms, exercises and projects; includes a primer on probability, a concise guide to the GPSS programming environment and an overview of relevant MATLAB features in the appendices; provides supplementary software and teaching support material at an associated website.

Dynamic Linear Models with R

Author: Giovanni Petris,Sonia Petrone,Patrizia Campagnoli

Publisher: Springer Science & Business Media

ISBN: 0387772383

Category: Mathematics

Page: 252

View: 9648

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State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

Modeling Complex Systems

Author: Nino Boccara

Publisher: Springer Science & Business Media

ISBN: 9781441965622

Category: Computers

Page: 490

View: 711

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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.