Optimal Quantification and Symmetry, Nishisato Shizuhiko

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: 19564.00 р.
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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: Soize Christian
Название: Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering
ISBN: 3319853724 ISBN-13(EAN): 9783319853727
Издательство: Springer
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Цена: 9083.00 р.
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Описание: An Accelerated Course with Applications in Computational Sciences and Engineering

Автор: Souza De Cursi Eduardo
Название: Uncertainty Quantification and Stochastic Modelling with Excel
ISBN: 3030777561 ISBN-13(EAN): 9783030777562
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.

Автор: Webber Jr Charles L., Ioana Cornel, Marwan Norbert
Название: Recurrence Plots and Their Quantifications: Expanding Horizons: Proceedings of the 6th International Symposium on Recurrence Plots, Grenoble, France,
ISBN: 3319806874 ISBN-13(EAN): 9783319806877
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The chapters in this book originate from the research work and contributions presented at the Sixth International Symposium on Recurrence Plots held in Grenoble, France in June 2015.

Автор: Jadamba
Название: Uncertainty Quantification In Varia
ISBN: 1138626325 ISBN-13(EAN): 9781138626324
Издательство: Taylor&Francis
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Цена: 16843.00 р.
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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.

Автор: Roger Ghanem; David Higdon; Houman Owhadi
Название: Handbook of Uncertainty Quantification
ISBN: 3319123858 ISBN-13(EAN): 9783319123851
Издательство: Springer
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Цена: 181680.00 р.
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Автор: Mcclarren, Ryan G.
Название: Uncertainty quantification and predictive computational science
ISBN: 3319995243 ISBN-13(EAN): 9783319995243
Издательство: Springer
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Цена: 13974.00 р.
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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: Raydugin Yuri G.
Название: Modern Risk Quantification in Complex Projects: Non-Linear Monte Carlo and System Dynamics Methodologies
ISBN: 0198844336 ISBN-13(EAN): 9780198844334
Издательство: Oxford Academ
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Цена: 27301.00 р.
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Описание: Offers a general participation assessment across five levels of participation and cooperation and the specific behaviours that make up these five levels. The manual details instructions on how to administer the Social Profile, describes how the assessment was developed, and summarized research to support its use. Also included are 14 case studies that illustrate how the Social Profile can be used.

Автор: Sullivan, T.j.
Название: Introduction to uncertainty quantification
ISBN: 3319794787 ISBN-13(EAN): 9783319794785
Издательство: Springer
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Цена: 8384.00 р.
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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.