Systems And Models

A multitude of complex systems and actors pursuing their own agenda shape the dynamics of our world. Better understanding of their actions and interactions is crucial, and can be achieved by a profound knowledge of systems and their properties, and their representation in models allowing simulation of probable behavior. Drawing on his extensive research and teaching experience in modeling and simulation of a wide range of systems - from engineering to social systems and ecosystems - the author presents the fundamental concepts and approaches for understanding and modeling the complex systems shaping the dynamics of our world. The book applies state space analysis and system dynamics to deal with the dynamic processes of "causal systems," discusses information processing approaches for modeling decision processes of "actors" and "agents," and uses aspects of the coevolutionary development of systems in their environment to deal with normative orientation, ethics, and evaluation of policies and long-term development. The concepts are applied in particular to the issue of sustainable development of human society in an evolving world. The book is complemented by a survey of system topics and of models from many fields, and by an extensive bibliography on the many systems-related subjects covered. Hartmut Bossel is Professor Emeritus of environmental systems analysis. He taught for many years at the University of California in Santa Barbara and the University of Kassel, Germany, where he was director of the Center for Environmental Systems Research until his retirement. He holds an engineering degree from the Technical University of Darmstadt, and a Ph.D. degree from the University of California at Berkeley. With a background in engineering, systems science, and mathematical modeling, he has led many research projects and future studies in different countries, developing computer simulation models and decision support systems in the areas of energy supply policy, global dynamics, orientation of behavior, agricultural policy, and forest dynamics and management. He has written numerous books on modeling and simulation of dynamic systems, social change and future paths, and has published widely in the scientific literature in several fields. Bossel is author of a System Zoo containing over one hundred simulation models of diverse systems.

This book presents a comprehensive compilation of practical systems engineering models. The application and recognition of systems engineering is spreading rapidly, however there is no book that addresses the availability and usability of systems engineering models. Notable among the models to be included are the V-Model, DEJI Model, and Waterfall Model. There are other models developed for specific organizational needs, which will be identified and presented in a practical template so that other organizations can learn and use them. A better understanding of the models, through a comprehensive book, will make these models more visible, embraced, and applied across the spectrum. Visit www.DEJImodel.com for model details. Features Covers applications to both small and large problems Displays decomposition of complex problems into smaller manageable chunks Discusses direct considerations of the pertinent constraints that exist in the problem domain Presents systematic linking of inputs to goals and outputs

This book concisely presents a broad range of models and theories on social systems. Because of the huge spectrum of topics involving social systems, various issues related to Mathematics, Statistics, Teaching, Social Science, and Economics are discussed. In an effort to introduce the subject to a wider audience, this volume, part of the series “Studies in Systems, Decision and Control”, equally addresses the needs of mathematicians, statisticians, sociologists and philosophers. The studies examined here are divided into four parts. The first part, “Perusing the Minds Behind Scientific Discoveries”, traces the winding path of Syamal K. Sen and Ravi P. Agarwal’s scholarship throughout history, and most importantly, the thought processes that allowed each of them to master their subject. The second part covers “Theories in Social Systems” and the third discusses “Models in Social Systems”, while the fourth and final part is dedicated to “Mathematical Methods in the Social Sciences”. Given its breadth of coverage, the book will offer inquisitive readers a valuable point of departure for exploring these rich, vast, and ever-expanding fields of knowledge.

This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.

In this book the authors introduce and explain many methods and models for the development of Information Systems (IS). It was written in large part to aid designers in designing successful devices/systems to match user needs in the field. Chief among these are website development, usability evaluation, quality evaluation and success assessment. The book provides great detail in order to assist readers’ comprehension and understanding of both novel and refined methodologies by presenting, describing, explaining and illustrating their basics and working mechanics. Furthermore, this book presents many traditional methods and methodologies in an effort to make up a comprehensive volume on High Level Models and Methodologies for Information Systems. The target audience for this book is anyone interested in conducting research in IS planning and development. The book represents a main source of theory and practice of IS methods and methodologies applied to these realities. The book will appeal to a range of professions that are involved in planning and building the information systems, for example information technologists, information systems developers, as well as Web designers and developers—both researchers and practitioners; as a consequence, this book represents a genuinely multi-disciplinary approach to the field of IS methods and methodologies.

This book at once introduces the entire area of adaptive modeling and precisely defines a new decision-making procedure for developing and using models of large, complex socioeconomic systems.

The purpose of this book is to expose undergraduate students to the use of applied mathematics and physical argument as a basis for developing an understanding of the response characteristics, from a systems viewpoint, of a broad class of dynamic physical processes. This book was developed for use in the course ECE 355, Dynamic Systems and Modeling, in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor. The course ECE 355 has been elected primarily by junior and senior level students in computer engineering or in electrical engineering. Occasionally a student from outside these two programs elected the course. Thus the book is written with this class of students in mind. It is assumed that the reader has previous background in mathematics through calculus, differential equations, and Laplace transforms, in elementary physics, and in elemen tary mechanics and circuits. Although these prerequisites indicate the orientation of the material, the book should be accessible and of interest to students with a much wider spectrum of experience in applied mathemati cal topics. The subject matter of the book can be considered to form an introduc tion to the theory of mathematical systems presented from a modern, as opposed to a classical, point of view. A number of physical processes are examined where the underlying systems concepts can be clearly seen and grasped. The organization of the book around case study examples has evolved as a consequence of student suggestions.

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.