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Author: Yakov Ben-Haim Publisher: Elsevier ISBN: 0080465706 Category : Computers Languages : en Pages : 385
Book Description
Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. Info-Gap Decision Theory is written for decision analysts. The term "decision analyst" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts, usually without calling themselves by this name. In addition to engineers, decision analysts work in planning offices for public agencies, in project management consultancies, they are engaged in manufacturing process planning and control, in financial planning and economic analysis, in decision support for medical or technological diagnosis, and so on and on. Decision analysts provide quantitative support for the decision-making process in all areas where systematic decisions are made. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas - especially biological conservation, economic policy formulation, preparedness against terrorism, and medical decision-making. Pertinent new examples have been included. Second, the combination of info-gap analysis with probabilistic decision algorithms has found wide application. Consequently "hybrid" models of uncertainty, which were treated exclusively in a separate chapter in the previous edition, now appear throughout the book as well as in a separate chapter. Finally, info-gap explanations of robust-satisficing behavior, and especially the Ellsberg and Allais "paradoxes", are discussed in a new chapter together with a theorem indicating when robust-satisficing will have greater probability of success than direct optimizing with uncertain models. - New theory developed systematically - Many examples from diverse disciplines - Realistic representation of severe uncertainty - Multi-faceted approach to risk - Quantitative model-based decision theory
Author: Yakov Ben-Haim Publisher: Elsevier ISBN: 0080465706 Category : Computers Languages : en Pages : 385
Book Description
Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. Info-Gap Decision Theory is written for decision analysts. The term "decision analyst" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts, usually without calling themselves by this name. In addition to engineers, decision analysts work in planning offices for public agencies, in project management consultancies, they are engaged in manufacturing process planning and control, in financial planning and economic analysis, in decision support for medical or technological diagnosis, and so on and on. Decision analysts provide quantitative support for the decision-making process in all areas where systematic decisions are made. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas - especially biological conservation, economic policy formulation, preparedness against terrorism, and medical decision-making. Pertinent new examples have been included. Second, the combination of info-gap analysis with probabilistic decision algorithms has found wide application. Consequently "hybrid" models of uncertainty, which were treated exclusively in a separate chapter in the previous edition, now appear throughout the book as well as in a separate chapter. Finally, info-gap explanations of robust-satisficing behavior, and especially the Ellsberg and Allais "paradoxes", are discussed in a new chapter together with a theorem indicating when robust-satisficing will have greater probability of success than direct optimizing with uncertain models. - New theory developed systematically - Many examples from diverse disciplines - Realistic representation of severe uncertainty - Multi-faceted approach to risk - Quantitative model-based decision theory
Author: Vincent A. W. J. Marchau Publisher: Springer ISBN: 3030052524 Category : Business & Economics Languages : en Pages : 408
Book Description
This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.
Author: Behnam Mohammadi-ivatloo Publisher: Springer ISBN: 3030042960 Category : Technology & Engineering Languages : en Pages : 319
Book Description
This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.
Author: Y. Ben-Haim Publisher: Springer ISBN: 0230277322 Category : Business & Economics Languages : en Pages : 257
Book Description
This book is a product of applying info-gap decision theory to policy formulation and evaluation in monetary economics and related domains. Info-gap theory has been applied to planning and decision problems in many areas, including engineering, biological conservation, project management, economics, medicine, homeland security, and more.
Author: Sayyad Nojavan Publisher: Academic Press ISBN: 0128174927 Category : Technology & Engineering Languages : en Pages : 295
Book Description
Risk-Based Energy Management: DC, AC and Hybrid AC-DC Microgrids defines the problems and challenges of DC, AC and hybrid AC-DC microgrids and considers the right tactics and risk-based scheduling to tackle them. The book looks at the intermittent nature of renewable generation, demand and market price with the risk to DC, AC and hybrid AC-DC microgrids, which makes it relevant for anyone in renewable energy demand and supply. As utilization of distributed energy resources and the intermittent nature of renewable generations, demand and market price can put the operation of DC, AC and hybrid AC-DC microgrids at risk, this book presents a timely resource. - Discusses both the challenges and solutions surrounding DC, AC and hybrid AC-DC microgrids - Proposes robust scheduling of DC, AC and hybrid AC-DC microgrids under uncertain environments - Includes modeling upstream grid prices, renewable resources and intermittent load in the decision-making process of DC, AC and hybrid AC-DC microgrids
Author: Jeffrey Pfeffer Publisher: Harvard Business Press ISBN: 9781578511242 Category : Business & Economics Languages : en Pages : 348
Book Description
The market for business knowledge is booming as companies looking to improve their performance pour millions of pounds into training programmes, consultants, and executive education. Why then, are there so many gaps between what firms know they should do and waht they actual do? This volume confronts the challenge of turning knowledge about how to improve performance into actions that produce measurable results. The authors identify the causes of this gap and explain how to close it.
Author: David J. C. MacKay Publisher: Cambridge University Press ISBN: 9780521642989 Category : Computers Languages : en Pages : 694
Book Description
Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Author: Ellen B. Mandinach Publisher: Corwin Press ISBN: 1412982049 Category : Business & Economics Languages : en Pages : 281
Book Description
"Gathering data and using it to inform instruction is a requirement for many schools, yet educators are not necessarily formally trained in how to do it. This book helps bridge the gap between classroom practice and the principles of educational psychology. Teachers will find cutting-edge advances in research and theory on human learning and teaching in an easily understood and transferable format. The text's integrated model shows teachers, school leaders, and district administrators how to establish a data culture and transform quantitative and qualitative data into actionable knowledge based on: assessment; statistics; instructional and differentiated psychology; classroom management."--Publisher's description.
Author: Gavin Bennett Publisher: IDRC ISBN: 8132105850 Category : Business & Economics Languages : en Pages : 285
Book Description
The Knowledge Translation Toolkit provides a thorough overview of what knowledge translation (KT) is and how to use it most effectively to bridge the "know-do" gap between research, policy, practice, and people. It presents the theories, tools, and strategies required to encourage and enable evidence-informed decision-making. This toolkit builds upon extensive research into the principles and skills of KT: its theory and literature, its evolution, strategies, and challenges. The book covers an array of crucial KT enablers--from context mapping to evaluative thinking--supported by practical examples, implementation guides, and references. Drawing from the experience of specialists in relevant disciplines around the world, The Knowledge Translation Toolkit aims to enhance the capacity and motivation of researchers to use KT and to use it well. The Tools in this book will help researchers ensure that their good science reaches more people, is more clearly understood, and is more likely to lead to positive action. In sum, their work becomes more useful, and therefore, more valuable.
Author: Hans-Jürgen Zimmermann Publisher: Springer Science & Business Media ISBN: 9400932499 Category : Business & Economics Languages : en Pages : 342
Book Description
In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.
Author: Yakov Ben-Haim
Author: Yakov Ben-Haim
Author: Vincent A. W. J. Marchau
Author: Behnam Mohammadi-ivatloo
Author: Y. Ben-Haim
Author: Sayyad Nojavan
Author: Jeffrey Pfeffer
Author: David J. C. MacKay
Author: Ellen B. Mandinach
Author: Gavin Bennett
Author: Hans-Jürgen Zimmermann