Whys and Hows in Uncertainty Modelling

Whys and Hows in Uncertainty Modelling
Author: Isaac Elishakoff
Publisher: Springer
Total Pages: 391
Release: 2014-05-04
Genre: Technology & Engineering
ISBN: 3709125014

This book presents, as a single package, three semingly contradictory and often competitive approaches to deal with ever present uncertainty in science and engineering. The book describes, as a unique view, probabilistic, fuzzy sets based and antioptimization based approaches, in order to remedy the present "tower ob Babel” situation, in which researchers in competing fields do not communicate. Integrative approach will attract scientists and engineers alike and provide a strong impetus towards integrative, hybrid approaches.

Uncertainty

Uncertainty
Author: William Briggs
Publisher: Springer
Total Pages: 274
Release: 2016-07-15
Genre: Mathematics
ISBN: 3319397567

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance." The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach
Author: Bilal Ayyub
Publisher: Springer Science & Business Media
Total Pages: 414
Release: 1997-10-31
Genre: Computers
ISBN: 9780792380306

Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

The Uncertainty Mindset

The Uncertainty Mindset
Author: Vaughn Tan
Publisher: Columbia University Press
Total Pages: 296
Release: 2020-07-28
Genre: Social Science
ISBN: 0231551878

Innovation is how businesses stay ahead of the competition and adapt to market conditions that change in unpredictable and uncertain ways. In the first decade of the twenty-first century, high-end cuisine underwent a profound transformation. Once an industry that prioritized consistency and reliability, it turned into one where constant change was a competitive necessity. A top restaurant’s reputation and success have become so closely bound up with its ability to innovate that a new organizational form, the culinary research and development team, has emerged. The best of these R&D teams continually expand the frontiers of food—they invent a constant stream of new dishes, new cooking processes and methods, and even new ways of experiencing food. How do they achieve this nonstop novelty? And what can culinary research and development teach us about how organizations innovate? Vaughn Tan opens up the black box of elite culinary R&D to provide essential insights. Drawing on years of unprecedented access to the best and most influential culinary R&D teams in the world, he reveals how they exemplify what he calls the uncertainty mindset. Such a mindset intentionally incorporates uncertainty into organization design rather than simply trying to reduce risk. It changes how organizations hire, set goals, and motivate team members and leads organizations to work in highly unconventional ways. A revelatory look at the R&D kitchen, The Uncertainty Mindset upends conventional wisdom about how to organize for innovation and offers practical insights for businesses trying to become innovative and adaptable.

Robust Optimization of Spline Models and Complex Regulatory Networks

Robust Optimization of Spline Models and Complex Regulatory Networks
Author: Ayşe Özmen
Publisher: Springer
Total Pages: 143
Release: 2016-05-11
Genre: Business & Economics
ISBN: 3319308009

This book introduces methods of robust optimization in multivariate adaptive regression splines (MARS) and Conic MARS in order to handle uncertainty and non-linearity. The proposed techniques are implemented and explained in two-model regulatory systems that can be found in the financial sector and in the contexts of banking, environmental protection, system biology and medicine. The book provides necessary background information on multi-model regulatory networks, optimization and regression. It presents the theory of and approaches to robust (conic) multivariate adaptive regression splines - R(C)MARS – and robust (conic) generalized partial linear models – R(C)GPLM – under polyhedral uncertainty. Further, it introduces spline regression models for multi-model regulatory networks and interprets (C)MARS results based on different datasets for the implementation. It explains robust optimization in these models in terms of both the theory and methodology. In this context it studies R(C)MARS results with different uncertainty scenarios for a numerical example. Lastly, the book demonstrates the implementation of the method in a number of applications from the financial, energy, and environmental sectors, and provides an outlook on future research.

Verification and Validation in Scientific Computing

Verification and Validation in Scientific Computing
Author: William L. Oberkampf
Publisher: Cambridge University Press
Total Pages: 782
Release: 2010-10-14
Genre: Computers
ISBN: 1139491768

Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.

Science and Judgment in Risk Assessment

Science and Judgment in Risk Assessment
Author: National Research Council
Publisher: National Academies Press
Total Pages: 668
Release: 1994-01-01
Genre: Science
ISBN: 030904894X

The public depends on competent risk assessment from the federal government and the scientific community to grapple with the threat of pollution. When risk reports turn out to be overblownâ€"or when risks are overlookedâ€"public skepticism abounds. This comprehensive and readable book explores how the U.S. Environmental Protection Agency (EPA) can improve its risk assessment practices, with a focus on implementation of the 1990 Clean Air Act Amendments. With a wealth of detailed information, pertinent examples, and revealing analysis, the volume explores the "default option" and other basic concepts. It offers two views of EPA operations: The first examines how EPA currently assesses exposure to hazardous air pollutants, evaluates the toxicity of a substance, and characterizes the risk to the public. The second, more holistic, view explores how EPA can improve in several critical areas of risk assessment by focusing on cross-cutting themes and incorporating more scientific judgment. This comprehensive volume will be important to the EPA and other agencies, risk managers, environmental advocates, scientists, faculty, students, and concerned individuals.

Forecasting Demand and Supply of Doctoral Scientists and Engineers

Forecasting Demand and Supply of Doctoral Scientists and Engineers
Author: National Research Council
Publisher: National Academies Press
Total Pages: 104
Release: 2000-07-31
Genre: Medical
ISBN: 0309171822

This report is the summary of a workshop conducted by the National Research Council in order to learn from both forecast makers and forecast users about improvements that can be made in understanding the markets for doctoral scientists and engineers. The workshop commissioned papers examined (1) the history and problems with models of demand and supply for scientists and engineers, (2) objectives and approaches to forecasting models, (3) margins of adjustment that have been neglected in models, especially substitution and quality, (4) the presentation of uncertainty, and (5) whether these forecasts of supply and demand are worthwhile, given all their shortcomings. The focus of the report was to provide guidance to the NSF and to scholars in this area on how models and the forecasts derived from them might be improved, and what role NSF should play in their improvement. In addition, the report examined issues of reporting forecasts to policymakers.

Modeling Uncertainty in the Earth Sciences

Modeling Uncertainty in the Earth Sciences
Author: Jef Caers
Publisher: John Wiley & Sons
Total Pages: 294
Release: 2011-05-25
Genre: Science
ISBN: 1119998719

Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; large complexity and dimensionality; computation power; costs of 'engineering' the Earth; uncertainty in the modeling and decision process. Focusing on reliable and practical methods this book provides an invaluable primer for the complex area of decision making with uncertainty in the Earth Sciences.