A Model-free Definition of Increasing Uncertainty PDF Download
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Author: Simon Grant
Publisher:
ISBN:
Category :
Languages : en
Pages : 27
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Book Description
Author: Simon Grant
Publisher:
ISBN:
Category :
Languages : en
Pages : 27
Get Book Here
Book Description
Author: Simon Grant
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Mohammed Abdellaoui
Publisher: Springer Science & Business Media
ISBN: 3540489355
Category : Business & Economics
Languages : en
Pages : 299
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Book Description
This book tries to sort out the different meanings of uncertainty and to discover their foundations. It shows that uncertainty can be represented using various tools and mental guidelines. Coverage also examines alternative ways to deal with risk and risk attitude concepts. Behavior under uncertainty emerges from this book as something to base more on inquiry and reflection rather than on mere intuition.
Author: Alexander K. Belyaev
Publisher: Springer Science & Business Media
ISBN: 9400702892
Category : Technology & Engineering
Languages : en
Pages : 471
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Book Description
The Symposium was aimed at the theoretical and numerical problems involved in modelling the dynamic response of structures which have uncertain properties due to variability in the manufacturing and assembly process, with automotive and aerospace structures forming prime examples. It is well known that the difficulty in predicting the response statistics of such structures is immense, due to the complexity of the structure, the large number of variables which might be uncertain, and the inevitable lack of data regarding the statistical distribution of these variables. The Symposium participants presented the latest thinking in this very active research area, and novel techniques were presented covering the full frequency spectrum of low, mid, and high frequency vibration problems. It was demonstrated that for high frequency vibrations the response statistics can saturate and become independent of the detailed distribution of the uncertain system parameters. A number of presentations exploited this physical behaviour by using and extending methods originally developed in both phenomenological thermodynamics and in the fields of quantum mechanics and random matrix theory. For low frequency vibrations a number of presentations focussed on parametric uncertainty modelling (for example, probabilistic models, interval analysis, and fuzzy descriptions) and on methods of propagating this uncertainty through a large dynamic model in an effi cient way. At mid frequencies the problem is mixed, and various hybrid schemes were proposed. It is clear that a comprehensive solution to the problem of predicting the vibration response of uncertain structures across the whole frequency range requires expertise across a wide range of areas (including probabilistic and non-probabilistic methods, interval and info-gap analysis, statistical energy analysis, statistical thermodynamics, random wave approaches, and large scale computations) and this IUTAM symposium presented a unique opportunity to bring together outstanding international experts in these fields.
Author: Haraldur Olafsson
Publisher: Elsevier
ISBN: 0128157100
Category : Science
Languages : en
Pages : 366
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Book Description
Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer. Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts. This is an essential work for anyone who wants to improve the accuracy of weather and climate forecasting and interested parties developing tools to enhance the quality of such forecasts. - Provides a comprehensive overview of the state of numerical weather prediction at spatial scales, from hundreds of meters, to thousands of kilometers - Focuses on short-term 1-15 day atmospheric predictions, with some coverage appropriate for longer-term forecasts - Includes references to climate prediction models to allow applications of these techniques for climate simulations
Author: Christian A. Schenk
Publisher: Springer Science & Business Media
ISBN: 9783540253433
Category : Technology & Engineering
Languages : en
Pages : 184
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Book Description
The treatment of uncertainties in the analysis of engineering structures remains one of the premium challenges in modern structural mechanics. It is only in recent years that the developments in stochastic and deterministic computational mechanics began to be synchronized. To foster these developments, novel computational procedures for the uncertainty assessment of large finite element systems are presented in this monograph. The stochastic input is modeled by the so-called Karhunen-Loève expansion, which is formulated in this context both for scalar and vector stochastic processes as well as for random fields. Particularly for strongly non-linear structures and systems the direct Monte Carlo simulation technique has proven to be most advantageous as method of solution. The capabilities of the developed procedures are demonstrated by showing some practical applications.
Author: Jan Peter Hessling
Publisher: BoD – Books on Demand
ISBN: 9535132792
Category : Computers
Languages : en
Pages : 228
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Book Description
Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.
Author: Michael A. Bean
Publisher: American Mathematical Soc.
ISBN: 0821847929
Category : Mathematics
Languages : en
Pages : 464
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Book Description
Covers the basic probability of distributions with an emphasis on applications from the areas of investments, insurance, and engineering. This book is suitable as a text for senior undergraduate and beginning graduate students in mathematics, statistics, actuarial science, finance, or engineering.
Author: Etienne de Rocquigny
Publisher: John Wiley & Sons
ISBN: 0470770740
Category : Mathematics
Languages : en
Pages : 364
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Book Description
Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledging industrial constraints. The approach presented can be applied to a range of different business contexts, from research or early design through to certification or in-service processes. The authors aim to foster optimal trade-offs between literature-referenced methodologies and the simplified approaches often inevitable in practice, owing to data, time or budget limitations of technical decision-makers. Uncertainty in Industrial Practice: Features recent uncertainty case studies carried out in the nuclear, air & space, oil, mechanical and civil engineering industries set in a common methodological framework. Presents methods for organizing and treating uncertainties in a generic and prioritized perspective. Illustrates practical difficulties and solutions encountered according to the level of complexity, information available and regulatory and financial constraints. Discusses best practice in uncertainty modeling, propagation and sensitivity analysis through a variety of statistical and numerical methods. Reviews recent standards, references and available software, providing an essential resource for engineers and risk analysts in a wide variety of industries. This book provides a guide to dealing with quantitative uncertainty in engineering and modelling and is aimed at practitioners, including risk-industry regulators and academics wishing to develop industry-realistic methodologies.
Author: Richard W. Morris
Publisher: Academic Press
ISBN: 0128120991
Category : Psychology
Languages : en
Pages : 486
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Book Description
Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. - Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform - Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction - Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making
