Uncertainty Quantification and Stochastic Modelling with Excel, Souza De Cursi Eduardo
Автор: Mcclarren, Ryan G. Название: Uncertainty quantification and predictive computational science ISBN: 3319995243 ISBN-13(EAN): 9783319995243 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.
Автор: Nishisato Shizuhiko, Beh Eric J., Lombardo Rosaria Название: Modern Quantification Theory: Joint Graphical Display, Biplots, and Alternatives ISBN: 9811624690 ISBN-13(EAN): 9789811624698 Издательство: Springer Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis.
Автор: Olivier Le Maitre; Omar M Knio Название: Spectral Methods for Uncertainty Quantification ISBN: 9400731922 ISBN-13(EAN): 9789400731929 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents applications of spectral methods to problems of uncertainty propagation and quantification in model-based computations, focusing on the computational and algorithmic features of these methods most useful in dealing with models based on partial differential equations, in particular models arising in simulations of fluid flows.
Автор: Sullivan, T.j. Название: Introduction to uncertainty quantification ISBN: 3319794787 ISBN-13(EAN): 9783319794785 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved.
Автор: Roger Ghanem; David Higdon; Houman Owhadi Название: Handbook of Uncertainty Quantification ISBN: 3319123858 ISBN-13(EAN): 9783319123851 Издательство: Springer Рейтинг: Цена: 1211200.00 T Наличие на складе: Поставка под заказ.
Автор: Sullivan, T.J. Название: Introduction to Uncertainty Quantification ISBN: 3319233947 ISBN-13(EAN): 9783319233949 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study.
Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.
Автор: Luis Chase Название: Uncertainty Quantification: Advances in Research and Applications ISBN: 1536148628 ISBN-13(EAN): 9781536148626 Издательство: Nova Science Рейтинг: Цена: 77080.00 T Наличие на складе: Невозможна поставка. Описание: In recent times, polynomial chaos expansion has emerged as a dominant technique to determine the response uncertainties of a system by propagating the uncertainties of the inputs. In this regard, the opening chapter of Uncertainty Quantification: Advances in Research and Applications, an intrusive approach called Galerkin Projection as well as non-intrusive approaches (such as pseudo-spectral projection and linear regression) are discussed.Next, the authors introduce a new methodology to determine the uncertainties of input parameters using CIRCE software to overcome the reliance on expert judgment. The goal is to determinate and evaluate the uncertainty bounds for physical models related to reflood model of MARS-KS code Vessel module (coupled with COBRA-TF) using both CIRCE and the experimental data of FEBA.Lastly, uncertainties related to rheological model parameters of skeletal muscles are modeled and analyzed, and available data are acquired and fused for hyperelastic constitutive model parameters with Neo-Hookean and Mooney-Rivlin formulations.
Автор: Nishisato Shizuhiko Название: Optimal Quantification and Symmetry ISBN: 981169169X ISBN-13(EAN): 9789811691690 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a unique new look at the familiar quantification theory from the point of view of mathematical symmetry and spatial symmetry.
Название: Development and quantification of sustainability indicators ISBN: 9811325553 ISBN-13(EAN): 9789811325557 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book highlights various methods for quantifying sustainability indicators using different indices. To date, numerous sustainability indicators encompassing either all three pillars (economic, environmental and social) or individual or joint indicators (e.g. environmental and social) have been developed and quantified. In addition to commonly developed indicators, which can be utilized for any industrial sector, sector-specific sustainability indicators are frequently used. Behind each indicator developed, there is a unique scientific model, method or assessment technique. This book explores and elaborates on such indicators, and on associated details such as the concept, development methodology, assessment technique, and applications of each indicator.
Автор: Jadamba Название: Uncertainty Quantification In Varia ISBN: 1138626325 ISBN-13(EAN): 9781138626324 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields.
