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.
Modelling and Simulation
Author: Bilash Kanti Bala,Fatimah Mohamed Arshad,Kusairi Mohd Noh
Category: Business & Economics
In the summer of 2002, the Office of Naval Research asked the Committee on Human Factors to hold a workshop on dynamic social network and analysis. The primary purpose of the workshop was to bring together scientists who represent a diversity of views and approaches to share their insights, commentary, and critiques on the developing body of social network analysis research and application. The secondary purpose was to provide sound models and applications for current problems of national importance, with a particular focus on national security. This workshop is one of several activities undertaken by the National Research Council that bears on the contributions of various scientific disciplines to understanding and defending against terrorism. The presentations were grouped in four sessions Social Network Theory Perspectives, Dynamic Social Networks, Metrics and Models, and Networked Worlds each of which concluded with a discussant-led roundtable discussion among the presenters and workshop attendees on the themes and issues raised in the session.
Workshop Summary and Papers
Author: Committee on Human Factors,Board on Human-Systems Integration,Division of Behavioral and Social Sciences and Education,National Research Council
Publisher: National Academies Press
Category: Technology & Engineering
This book constitutes the refereed proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, held in College Park, MD, USA, March 29-31, 2011. The 48 papers and 3 keynotes presented in this volume were carefully reviewed and selected from 88 submissions. The papers cover a wide range of topics including social network analysis; modeling; machine learning and data mining; social behaviors; public health; cultural aspects; and effects and search.
4th International Conference, SBP 2011, College Park, MD, USA, March 29-31, 2011. Proceedings
Author: John Salerno,Shanchieh Jay Yang,Dana Nau,Sun-Ki Chai
Publisher: Springer Science & Business Media
Category: Business & Economics
Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
Author: Eric D. Kolaczyk,Gábor Csárdi
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
Author: Hazhir Rahmandad,Rogelio Oliva,Nathaniel D. Osgood,George Richardson
Publisher: MIT Press
Category: Business & Economics
With NATO's bombing campaign against Serbia now over, what strategic, long-range plans will the alliance employ to restore stability to the region? As the global economy continually changes in response to worldwide events, what investment strategies will firms implement to cope with changing markets? And how can major pharmaceutical companies solve the problem of having newly-developed products abandoned before they can even be launched on the market? This book is designed and written to give the applied statistician an insight into all these areas of investigation.
A PRACTICAL APPROACH
Author: R.G. Coyle
Publisher: CRC Press
Category: Business & Economics
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.
Author: Anna Goldenberg,Alice X. Zheng,Stephen E. Fienberg,Edoardo M. Airoldi
Publisher: Now Publishers Inc
This book constitutes the thoroughly refereed proceedings of the 7th International Workshop on Multi-Agent-Based Simulation, MABS 2006. This was held in Hakodate, Japan, May 8, 2006 as an associated event of AAMAS 2006, the main international conference on autonomous agents and multi-agent systems. The 12 revised full papers presented together with three short papers and two invited papers were carefully reviewed and selected from 25 submissions during two rounds of reviewing.
International Workshop, MABS 2006, Hakodate, Japan, May 8, 2006, Revised and Invited Papers
Author: Luis Antunes,Keiki Takadama
Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)
Author: Michael J. Crawley
Publisher: John Wiley & Sons
This book is based on presentations at AE’2006 (Aalborg, Denmark) – the second symposium on Artificial Economics. As a new constructive simulation method, Agent-Based Computational Economics (ACE) has in recent years proven its strength and applicability. Coverage in this volume extends to well known questions of economics, like the existence of market efficiency, and to questions raised by new analytical tools, for example networks of social interaction.
The Economy as a Complex Dynamic System
Author: Charlotte Bruun
Publisher: Springer Science & Business Media
Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment, 3e, is a complete guide to working with dynamic system models, with emphasis on models in agronomy and environmental science. The introductory section presents the foundational information for the book including the basics of system models, simulation, the R programming language, and the statistical notions necessary for working with system models. The most important methods of working with dynamic system models, namely uncertainty and sensitivity analysis, model calibration (frequentist and Bayesian), model evaluation, and data assimilation are all treated in detail, in individual chapters. New chapters cover the use of multi-model ensembles, the creation of metamodels that emulate the more complex dynamic system models, the combination of genetic and environmental information in gene-based crop models, and the use of dynamic system models to aid in sampling. The book emphasizes both understanding and practical implementation of the methods that are covered. Each chapter simply and clearly explains the underlying principles and assumptions of each method that is presented, with numerous examples and illustrations. R code for applying the methods is given throughout. This code is designed so that it can be adapted relatively easily to new problems. An expanded introductory section presents the basics of dynamic system modeling, with numerous examples from multiple fields, plus chapters on numerical simulation, statistics for modelers, and the R language. Covers in detail the basic methods: uncertainty and sensitivity analysis, model calibration (both frequentist and Bayesian), model evaluation, and data assimilation. Every method chapter has numerous examples of applications based on real problems, as well as detailed instructions for applying the methods to new problems using R. Each chapter has multiple exercises for self-testing or for classroom use. An R package with much of the code from the book can be freely downloaded from the CRAN package repository.
Methods, Tools and Examples for Agriculture and Environment
Author: Daniel Wallach,David Makowski,James W. Jones,Francois Brun
Publisher: Academic Press
divThis book explores community dynamics within social media. Using Wikipedia as an example, the volume explores communities that rely upon commons-based peer production. Fundamental theoretical principles spanning such domains as organizational configurations, leadership roles, and social evolutionary theory are developed. In the context of Wikipedia, these theories explain how a functional elite of highly productive editors has emerged and why they are responsible for a majority of the content. It explains how the elite shapes the project and how this group tends to become stable and increasingly influential over time. Wikipedia has developed a new and resilient social hierarchy, an adhocracy, which combines features of traditional and new, online, social organizations. The book presents a set of practical approaches for using these theories in real-world practice. This work fundamentally changes the way we think about social media leadership and evolution, emphasizing the crucial contributions of leadership, of elite social roles, and of group global structure to the overall success and stability of large social media projects. Written in an accessible and direct style, the book will be of interest to academics as well as professionals with an interest in social media and commons-based peer production processes.
Adhocracy, Entropy, and the "1 % Effect"
Author: Sorin Adam Matei,Brian C. Britt
In this volume recent advances in the use of modern quantitative models for the analysis of various problems related to the dynamics of social and economic systems are presented. The majority chapters describe tools and techniques of broadly perceived computational intelligence, notably fuzzy logic, evolutionary computation, neural networks and some non-standard probabilistic and statistical analyses. Due to the high complexity of the systems and problems considered, in many situations it is necessary to consider at the same time analytic, topological and statistical aspects and apply appropriate procedures and algorithms. This volume is a direct result of vivid discussions held during the Fifth International Workshop on Dynamics of Social and Economical Systems (DYSES) which was held at Benevento, Italy September 20-25, 2010, as well as a couple of post-workshop meetings and consultations.
Author: Araceli N. Proto,Massimo Squillante,Janusz Kacprzyk
This book covers the modelling of human behaviour in the education and labour markets, which due to their interdependency are viewed as one system. Important factors influencing the decision-making of individuals and firms in this system are discussed. The role of social environment and networks is stressed. The approach of agent-based modelling is presented and compared with standard economic modelling and other simulation techniques in the context of modelling complex adaptive systems. Practical questions in building agent-based models of labour–education market system with social networks are discussed. These questions include modelling the structure of education system and agent behaviour there; modelling and calibrating the labour market without and with firms; generating the social network, defining its behaviour and calibrating it; and embedding the resulting system into a larger model.
Author: Alexander Tarvid
Category: Business & Economics
This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.
Author: Remco van der Hofstad
Publisher: Cambridge University Press
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Methods and Models
Author: Eric D. Kolaczyk
Publisher: Springer Science & Business Media
This monograph presents urban simulation methods that help in better understanding urban dynamics. Over historical times, cities have progressively absorbed a larger part of human population and will concentrate three quarters of humankind before the end of the century. This “urban transition” that has totally transformed the way we inhabit the planet is globally understood in its socio-economic rationales but is less frequently questioned as a spatio-temporal process. However, the cities, because they are intrinsically linked in a game of competition for resources and development, self organize in “systems of cities” where their future becomes more and more interdependent. The high frequency and intensity of interactions between cities explain that urban systems all over the world exhibit large similarities in their hierarchical and functional structure and rather regular dynamics. They are complex systems whose emergence, structure and further evolution are widely governed by the multiple kinds of interaction that link the various actors and institutions investing in cities their efforts, capital, knowledge and intelligence. Simulation models that reconstruct this dynamics may help in better understanding it and exploring future plausible evolutions of urban systems. This would provide better insight about how societies can manage the ecological transition at local, regional and global scales. The author has developed a series of instruments that greatly improve the techniques of validation for such models of social sciences that can be submitted to many applications in a variety of geographical situations. Examples are given for several BRICS countries, Europe and United States. The target audience primarily comprises research experts in the field of urban dynamics, but the book may also be beneficial for graduate students.
Author: Denise Pumain,Romain Reuillon
Category: Political Science
This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive information. Next, we describe some privacy definitions and privacy mechanisms for data publishing. Finally, we describe a set of recent techniques for modeling, evaluating, and managing individual users' privacy risk within the context of OSNs. Table of Contents: Introduction / A Model for Online Social Networks / Types of Privacy Disclosure / Statistical Methods for Inferring Information in Networks / Anonymity and Differential Privacy / Attacks and Privacy-preserving Mechanisms / Models of Information Sharing / Users' Privacy Risk / Management of Privacy Settings
Author: Elena Zheleva,Evimaria Terzi,Lise Getoor
Publisher: Morgan & Claypool Publishers
In this new century mankind faces ever more challenging environmental and publichealthproblems,suchaspollution,invasionbyexoticspecies,theem- gence of new diseases or the emergence of diseases into new regions (West Nile virus,SARS,Anthrax,etc.),andtheresurgenceofexistingdiseases(in?uenza, malaria, TB, HIV/AIDS, etc.). Mathematical models have been successfully used to study many biological, epidemiological and medical problems, and nonlinear and complex dynamics have been observed in all of those contexts. Mathematical studies have helped us not only to better understand these problems but also to ?nd solutions in some cases, such as the prediction and control of SARS outbreaks, understanding HIV infection, and the investi- tion of antibiotic-resistant infections in hospitals. Structuredpopulationmodelsdistinguishindividualsfromoneanother- cording to characteristics such as age, size, location, status, and movement, to determine the birth, growth and death rates, interaction with each other and with environment, infectivity, etc. The goal of structured population models is to understand how these characteristics a?ect the dynamics of these models and thus the outcomes and consequences of the biological and epidemiolo- cal processes. There is a very large and growing body of literature on these topics. This book deals with the recent and important advances in the study of structured population models in biology and epidemiology. There are six chapters in this book, written by leading researchers in these areas.
Author: Pierre Magal,Shigui Ruan