Model Uncertainty

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The Uncertainty Analysis of Model Results

Author : Eduard Hofer
Publisher : Springer
ISBN 13 : 9783319762968
Total Pages : 346 pages
Book Rating : 4.7/5 (629 download)

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Book Synopsis The Uncertainty Analysis of Model Results by : Eduard Hofer

Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-07-01 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.

Modeling Uncertainty with Fuzzy Logic

Author : Asli Celikyilmaz
Publisher : Springer
ISBN 13 : 3540899243
Total Pages : 443 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Modeling Uncertainty with Fuzzy Logic by : Asli Celikyilmaz

Download or read book Modeling Uncertainty with Fuzzy Logic written by Asli Celikyilmaz and published by Springer. This book was released on 2009-04-01 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.

Uncertainty

Author : William Briggs
Publisher : Springer
ISBN 13 : 3319397567
Total Pages : 274 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Uncertainty by : William Briggs

Download or read book Uncertainty written by William Briggs and published by Springer. This book was released on 2016-07-15 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modeling Uncertainty

Author : Moshe Dror
Publisher : Springer
ISBN 13 : 9781475783698
Total Pages : 770 pages
Book Rating : 4.7/5 (836 download)

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Book Synopsis Modeling Uncertainty by : Moshe Dror

Download or read book Modeling Uncertainty written by Moshe Dror and published by Springer. This book was released on 2014-03-24 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum, it is a book of considerable interest to a broad range of academic researchers and students of stochastic systems.

Uncertainty Modeling for Engineering Applications

Author : Flavio Canavero
Publisher : Springer
ISBN 13 : 9783030048693
Total Pages : 0 pages
Book Rating : 4.0/5 (486 download)

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Book Synopsis Uncertainty Modeling for Engineering Applications by : Flavio Canavero

Download or read book Uncertainty Modeling for Engineering Applications written by Flavio Canavero and published by Springer. This book was released on 2019-01-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change. Written by leading international experts from different fields, the book demonstrates the unifying property of UQ theme that can be profitably adopted to solve problems of different domains. The collection in one place of different methodologies for different applications has the great value of stimulating the cross-fertilization and alleviate the language barrier among areas sharing a common background of mathematical modeling for problem solution. The book is designed for researchers, professionals and graduate students interested in quantitatively assessing the effects of uncertainties in their fields of application. The contents build upon the workshop “Uncertainty Modeling for Engineering Applications” (UMEMA 2017), held in Torino, Italy in November 2017.

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

Author : Bilal Ayyub
Publisher : Springer Science & Business Media
ISBN 13 : 9780792380306
Total Pages : 414 pages
Book Rating : 4.3/5 (83 download)

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Book Synopsis Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach by : Bilal Ayyub

Download or read book Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach written by Bilal Ayyub and published by Springer Science & Business Media. This book was released on 1997-10-31 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Uncertainty Quantification in Multiscale Materials Modeling

Author : Yan Wang
Publisher : Woodhead Publishing
ISBN 13 : 0081029411
Total Pages : 604 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Uncertainty Quantification in Multiscale Materials Modeling by : Yan Wang

Download or read book Uncertainty Quantification in Multiscale Materials Modeling written by Yan Wang and published by Woodhead Publishing. This book was released on 2020-03-12 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.

Modeling Uncertainty in the Earth Sciences

Author : Jef Caers
Publisher : John Wiley & Sons
ISBN 13 : 1119998719
Total Pages : 294 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Modeling Uncertainty in the Earth Sciences by : Jef Caers

Download or read book Modeling Uncertainty in the Earth Sciences written by Jef Caers and published by John Wiley & Sons. This book was released on 2011-05-25 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modeling and Inverse Problems in the Presence of Uncertainty

Author : H. T. Banks
Publisher : CRC Press
ISBN 13 : 1482206439
Total Pages : 403 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Modeling and Inverse Problems in the Presence of Uncertainty by : H. T. Banks

Download or read book Modeling and Inverse Problems in the Presence of Uncertainty written by H. T. Banks and published by CRC Press. This book was released on 2014-04-01 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the authors' own substantial projects-on uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation i

Probability and Bayesian Modeling

Author : Jim Albert
Publisher : CRC Press
ISBN 13 : 1351030132
Total Pages : 553 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Probability and Bayesian Modeling by : Jim Albert

Download or read book Probability and Bayesian Modeling written by Jim Albert and published by CRC Press. This book was released on 2019-12-06 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors’ research. This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection. The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book. A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.

Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses

Author : Wenzhong Shi
Publisher : CRC Press
ISBN 13 : 1420059289
Total Pages : 456 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses by : Wenzhong Shi

Download or read book Principles of Modeling Uncertainties in Spatial Data and Spatial Analyses written by Wenzhong Shi and published by CRC Press. This book was released on 2009-09-30 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: When compared to classical sciences such as math, with roots in prehistory, and physics, with roots in antiquity, geographical information science (GISci) is the new kid on the block. Its theoretical foundations are therefore still developing and data quality and uncertainty modeling for spatial data and spatial analysis is an important branch of t

Uncertainty Theory

Author : Baoding Liu
Publisher : Springer Science & Business Media
ISBN 13 : 3642139582
Total Pages : 350 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Uncertainty Theory by : Baoding Liu

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer Science & Business Media. This book was released on 2011-11-07 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Modeling Uncertainty with Fuzzy Logic

Author : Asli Celikyilmaz
Publisher : Springer Science & Business Media
ISBN 13 : 3540899235
Total Pages : 443 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Modeling Uncertainty with Fuzzy Logic by : Asli Celikyilmaz

Download or read book Modeling Uncertainty with Fuzzy Logic written by Asli Celikyilmaz and published by Springer Science & Business Media. This book was released on 2009-04-08 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world we live in is pervaded with uncertainty and imprecision. Is it likely to rain this afternoon? Should I take an umbrella with me? Will I be able to find parking near the campus? Should I go by bus? Such simple questions are a c- mon occurrence in our daily lives. Less simple examples: What is the probability that the price of oil will rise sharply in the near future? Should I buy Chevron stock? What are the chances that a bailout of GM, Ford and Chrysler will not s- ceed? What will be the consequences? Note that the examples in question involve both uncertainty and imprecision. In the real world, this is the norm rather than exception. There is a deep-seated tradition in science of employing probability theory, and only probability theory, to deal with uncertainty and imprecision. The mon- oly of probability theory came to an end when fuzzy logic made its debut. H- ever, this is by no means a widely accepted view. The belief persists, especially within the probability community, that probability theory is all that is needed to deal with uncertainty. To quote a prominent Bayesian, Professor Dennis Lindley, “The only satisfactory description of uncertainty is probability.

Natural Hazard Uncertainty Assessment

Author : Karin Riley
Publisher : John Wiley & Sons
ISBN 13 : 1119027861
Total Pages : 356 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Natural Hazard Uncertainty Assessment by : Karin Riley

Download or read book Natural Hazard Uncertainty Assessment written by Karin Riley and published by John Wiley & Sons. This book was released on 2016-12-12 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include: Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included Targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty Emphasis on the impacts of climate change on natural hazard processes and outcomes Recommendations for cross-disciplinary and science transfer across natural hazard sciences This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists. Read an interview with the editors to find out more: https://eos.org/editors-vox/reducing-uncertainty-in-hazard-prediction

Uncertainty Modeling

Author : Vladik Kreinovich
Publisher : Springer
ISBN 13 : 3319510525
Total Pages : 298 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Uncertainty Modeling by : Vladik Kreinovich

Download or read book Uncertainty Modeling written by Vladik Kreinovich and published by Springer. This book was released on 2017-01-31 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book commemorates the 65th birthday of Dr. Boris Kovalerchuk, and reflects many of the research areas covered by his work. It focuses on data processing under uncertainty, especially fuzzy data processing, when uncertainty comes from the imprecision of expert opinions. The book includes 17 authoritative contributions by leading experts.

Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems

Author : Chakraverty, S.
Publisher : IGI Global
ISBN 13 : 1466649925
Total Pages : 442 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems by : Chakraverty, S.

Download or read book Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems written by Chakraverty, S. and published by IGI Global. This book was released on 2014-01-31 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides the reader with basic concepts for soft computing and other methods for various means of uncertainty in handling solutions, analysis, and applications"--Provided by publisher.

Uncertainty Theory

Author : Baoding Liu
Publisher : Springer
ISBN 13 : 3540731652
Total Pages : 263 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Uncertainty Theory by : Baoding Liu

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer. This book was released on 2007-09-14 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. For this new edition the entire text has been totally rewritten. The chapters on chance theory and uncertainty theory are completely new. Mathematicians, researchers, engineers, designers, and students will find this work a stimulating and useful reference.