Uncertainty Quantification And Stochastic Modeling With Matlab

Author : Eduardo Souza de Cursi,Rubens Sampaio
Publisher : Unknown
Page : 0 pages
File Size : 46,9 Mb
Release : 2015
Category : Stochastic models
ISBN : OCLC:1336710255

Get Book

Uncertainty Quantification and Stochastic Modeling with Matlab by Eduardo Souza de Cursi,Rubens Sampaio Pdf

Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with many real-world applications within statistics, mathematics, probability and engineering, but also within the natural sciences. Literature on the topic has up until now been largely based on polynomial chaos, which raises difficulties when considering different types of approximation and does not lead to a unified presentation of the methods. Moreover, this description does not consider either deterministic problems or infinite dimensional ones. This book gives a unified, practical and comprehensive presentation of the main techniques used for the characterization of the effect of uncertainty on numerical models and on their exploitation in numerical problems. In particular, applications to linear and nonlinear systems of equations, differential equations, optimization and reliability are presented. Applications of stochastic methods to deal with deterministic numerical problems are also discussed. Matlab illustrates the implementation of these methods and makes the book suitable as a textbook and for self-study

Author : Eduardo Souza de Cursi,Rubens Sampaio
Publisher : Elsevier
Page : 456 pages
File Size : 54,8 Mb
Release : 2015-04-09
Category : Mathematics
ISBN : 9780081004715

Get Book

Uncertainty Quantification and Stochastic Modeling with Matlab by Eduardo Souza de Cursi,Rubens Sampaio Pdf

Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with many real-world applications within statistics, mathematics, probability and engineering, but also within the natural sciences. Literature on the topic has up until now been largely based on polynomial chaos, which raises difficulties when considering different types of approximation and does not lead to a unified presentation of the methods. Moreover, this description does not consider either deterministic problems or infinite dimensional ones. This book gives a unified, practical and comprehensive presentation of the main techniques used for the characterization of the effect of uncertainty on numerical models and on their exploitation in numerical problems. In particular, applications to linear and nonlinear systems of equations, differential equations, optimization and reliability are presented. Applications of stochastic methods to deal with deterministic numerical problems are also discussed. Matlab® illustrates the implementation of these methods and makes the book suitable as a textbook and for self-study. Discusses the main ideas of Stochastic Modeling and Uncertainty Quantification using Functional Analysis Details listings of Matlab® programs implementing the main methods which complete the methodological presentation by a practical implementation Construct your own implementations from provided worked examples

Author : José Eduardo Souza De Cursi
Publisher : Springer Nature
Page : 472 pages
File Size : 43,9 Mb
Release : 2020-08-19
Category : Technology & Engineering
ISBN : 9783030536695

Get Book

Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling by José Eduardo Souza De Cursi Pdf

This proceedings book discusses state-of-the-art research on uncertainty quantification in mechanical engineering, including statistical data concerning the entries and parameters of a system to produce statistical data on the outputs of the system. It is based on papers presented at Uncertainties 2020, a workshop organized on behalf of the Scientific Committee on Uncertainty in Mechanics (Mécanique et Incertain) of the AFM (French Society of Mechanical Sciences), the Scientific Committee on Stochastic Modeling and Uncertainty Quantification of the ABCM (Brazilian Society of Mechanical Sciences) and the SBMAC (Brazilian Society of Applied Mathematics).

Author : José Eduardo Souza De Cursi
Publisher : Springer Nature
Page : 282 pages
File Size : 49,9 Mb
Release : 2023-10-21
Category : Technology & Engineering
ISBN : 9783031470363

Get Book

Proceedings of the 6th International Symposium on Uncertainty Quantification and Stochastic Modelling by José Eduardo Souza De Cursi Pdf

This proceedings book covers a wide range of topics related to uncertainty analysis and its application in various fields of engineering and science. It explores uncertainties in numerical simulations for soil liquefaction potential, the toughness properties of construction materials, experimental tests on cyclic liquefaction potential, and the estimation of geotechnical engineering properties for aerogenerator foundation design. Additionally, the book delves into uncertainties in concrete compressive strength, bio-inspired shape optimization using isogeometric analysis, stochastic damping in rotordynamics, and the hygro-thermal properties of raw earth building materials. It also addresses dynamic analysis with uncertainties in structural parameters, reliability-based design optimization of steel frames, and calibration methods for models with dependent parameters. The book further explores mechanical property characterization in 3D printing, stochastic analysis in computational simulations, probability distribution in branching processes, data assimilation in ocean circulation modeling, uncertainty quantification in climate prediction, and applications of uncertainty quantification in decision problems and disaster management. This comprehensive collection provides insights into the challenges and solutions related to uncertainty in various scientific and engineering contexts.

Author : Eduardo Souza de Cursi
Publisher : Springer Nature
Page : 493 pages
File Size : 45,6 Mb
Release : 2024-06-10
Category : Electronic
ISBN : 9783031482083

Get Book

Uncertainty Quantification with R by Eduardo Souza de Cursi Pdf

Author : Nan Chen
Publisher : Springer Nature
Page : 208 pages
File Size : 40,7 Mb
Release : 2023-03-13
Category : Mathematics
ISBN : 9783031222498

Get Book

Stochastic Methods for Modeling and Predicting Complex Dynamical Systems by Nan Chen Pdf

This book enables readers to understand, model, and predict complex dynamical systems using new methods with stochastic tools. The author presents a unique combination of qualitative and quantitative modeling skills, novel efficient computational methods, rigorous mathematical theory, as well as physical intuitions and thinking. An emphasis is placed on the balance between computational efficiency and modeling accuracy, providing readers with ideas to build useful models in practice. Successful modeling of complex systems requires a comprehensive use of qualitative and quantitative modeling approaches, novel efficient computational methods, physical intuitions and thinking, as well as rigorous mathematical theories. As such, mathematical tools for understanding, modeling, and predicting complex dynamical systems using various suitable stochastic tools are presented. Both theoretical and numerical approaches are included, allowing readers to choose suitable methods in different practical situations. The author provides practical examples and motivations when introducing various mathematical and stochastic tools and merges mathematics, statistics, information theory, computational science, and data science. In addition, the author discusses how to choose and apply suitable mathematical tools to several disciplines including pure and applied mathematics, physics, engineering, neural science, material science, climate and atmosphere, ocean science, and many others. Readers will not only learn detailed techniques for stochastic modeling and prediction, but will develop their intuition as well. Important topics in modeling and prediction including extreme events, high-dimensional systems, and multiscale features are discussed.

Author : Eduardo Souza de Cursi
Publisher : Springer Nature
Page : 768 pages
File Size : 50,5 Mb
Release : 2023-02-22
Category : Business & Economics
ISBN : 9783031177859

Get Book

Uncertainty Quantification using R by Eduardo Souza de Cursi Pdf

This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments at the level necessary to make the presentation rigorous and the assumptions clearly established, while maintaining a focus on practical applications of uncertainty quantification methods. Practical aspects of applied probability are also discussed, making the content accessible to students. The introduction of R and Python allows the reader to solve more complex problems involving a more significant number of variables. Users will be able to use examples laid out in the text to solve medium-sized problems. The list of topics covered in this volume includes linear and nonlinear programming, Lagrange multipliers (for sensitivity), multi-objective optimization, game theory, as well as linear algebraic equations, and probability and statistics. Blending theoretical rigor and practical applications, this volume will be of interest to professionals, researchers, graduate and undergraduate students interested in the use of uncertainty quantification techniques within the framework of operations research and mathematical programming, for applications in management and planning.

Author : Flavio Canavero
Publisher : Springer
Page : 184 pages
File Size : 54,8 Mb
Release : 2018-12-29
Category : Technology & Engineering
ISBN : 9783030048709

Get Book

Uncertainty Modeling for Engineering Applications by Flavio Canavero Pdf

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.

Author : Hoai An Le Thi,Hoai Minh Le,Tao Pham Dinh
Publisher : Springer
Page : 1164 pages
File Size : 45,8 Mb
Release : 2019-06-15
Category : Technology & Engineering
ISBN : 9783030218034

Get Book

Optimization of Complex Systems: Theory, Models, Algorithms and Applications by Hoai An Le Thi,Hoai Minh Le,Tao Pham Dinh Pdf

This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July 8–10, 2019 at University of Lorraine, Metz, France. The book covers both theoretical and algorithmic aspects of Nonconvex Optimization, as well as its applications to modeling and solving decision problems in various domains. It is composed of 10 parts, each of them deals with either the theory and/or methods in a branch of optimization such as Continuous optimization, DC Programming and DCA, Discrete optimization & Network optimization, Multiobjective programming, Optimization under uncertainty, or models and optimization methods in a specific application area including Data science, Economics & Finance, Energy & Water management, Engineering systems, Transportation, Logistics, Resource allocation & Production management. The researchers and practitioners working in Nonconvex Optimization and several application areas can find here many inspiring ideas and useful tools & techniques for their works.

Author : Orestes Llanes Santiago,Carlos Cruz Corona,Antônio José Silva Neto,José Luis Verdegay
Publisher : Springer Nature
Page : 301 pages
File Size : 52,7 Mb
Release : 2020-02-14
Category : Technology & Engineering
ISBN : 9783030344092

Get Book

Computational Intelligence in Emerging Technologies for Engineering Applications by Orestes Llanes Santiago,Carlos Cruz Corona,Antônio José Silva Neto,José Luis Verdegay Pdf

This book explores applications of computational intelligence in key and emerging fields of engineering, especially with regard to condition monitoring and fault diagnosis, inverse problems, decision support systems and optimization. These applications can be beneficial in a broad range of contexts, including: water distribution networks, manufacturing systems, production and storage of electrical energy, heat transfer, acoustic levitation, uncertainty and robustness of infinite-dimensional objects, fatigue failure prediction, autonomous navigation, nanotechnology, and the analysis of technological development indexes. All applications, mathematical and computational tools, and original results are presented using rigorous mathematical procedures. Further, the book gathers contributions by respected experts from 22 different research centers and eight countries: Brazil, Cuba, France, Hungary, India, Japan, Romania and Spain. The book is intended for use in graduate courses on applied computation, applied mathematics, and engineering, where tools like computational intelligence and numerical methods are applied to the solution of real-world problems in emerging areas of engineering.

Author : Eduardo Souza de Cursi
Publisher : John Wiley & Sons
Page : 430 pages
File Size : 54,9 Mb
Release : 2015-10-02
Category : Mathematics
ISBN : 9781119230151

Get Book

Variational Methods for Engineers with Matlab by Eduardo Souza de Cursi Pdf

This book is issued from a 30 years’ experience on the presentation of variational methods to successive generations of students and researchers in Engineering. It gives a comprehensive, pedagogical and engineer-oriented presentation of the foundations of variational methods and of their use in numerical problems of Engineering. Particular applications to linear and nonlinear systems of equations, differential equations, optimization and control are presented. MATLAB programs illustrate the implementation and make the book suitable as a textbook and for self-study. The evolution of knowledge, of the engineering studies and of the society in general has led to a change of focus from students and researchers. New generations of students and researchers do not have the same relations to mathematics as the previous ones. In the particular case of variational methods, the presentations used in the past are not adapted to the previous knowledge, the language and the centers of interest of the new generations. Since these methods remain a core knowledge – thus essential - in many fields (Physics, Engineering, Applied Mathematics, Economics, Image analysis ...), a new presentation is necessary in order to address variational methods to the actual context.

Author : Bruce G. Marcot
Publisher : CRC Press
Page : 278 pages
File Size : 49,9 Mb
Release : 2020-11-26
Category : Business & Economics
ISBN : 9781000244519

Get Book

The Science and Management of Uncertainty by Bruce G. Marcot Pdf

Uncertainty can take many forms, can be represented in many ways, and can have important implications in decision-making and policy development. This book provides a rigorous scientific framework for dealing with uncertainty in real-world situations, and provides a comprehensive study of concepts, measurements, and applications of uncertainty in ecological modeling and natural resource management. The focus of this book is on the kinds and implications of uncertainty in environmental modeling and management, with practical guidelines and examples for successful modeling and risk analysis in the face of uncertain conditions and incomplete information. Provided is a clear classification of uncertainty; methods for measuring, modeling, and communicating uncertainty; practical guidelines for capturing and representing expert knowledge and judgment; explanations of the role of uncertainty in decision-making; a guideline to avoiding logical fallacies when dealing with uncertainty; and several example cases of real-world ecological modeling and risk analysis to illustrate the concepts and approaches. Case topics provide examples of structured decision-making, statistical modeling, and related topics. A summary provides practical next steps that the reader can take in analyzing and interpreting uncertainty in real-world situations. Also provided is a glossary and a suite of references.

Author : Vladimir Raizer,Isaac Elishakoff
Publisher : CRC Press
Page : 266 pages
File Size : 46,8 Mb
Release : 2022-07-28
Category : Technology & Engineering
ISBN : 9781000550740

Get Book

Philosophies of Structural Safety and Reliability by Vladimir Raizer,Isaac Elishakoff Pdf

Uncertainty is certain to be found in structural engineering, making it crucial to structure design. This book covers three competing philosophies behind structural safety and reliability: probabilistic analysis, fuzzy set-based treatments, and the convex approach. Explaining the theory behind probabilistic analysis, fuzzy set-based treatments, and the convex approach in detail, alongside their implementation, use, and benefits, the book compares and contrasts these methods, enabling the reader to solve problems associated with uncertainty. These uncertainty issues can be seen in civil engineering structures, risk of earthquakes, impact of rough seas on ships, and turbulence affecting aerospace vehicles. Building on the authors’ many years of experience in the field, Philosophies of Structural Safety and Reliability is an essential guide to structural uncertainty. Topics covered in the book include properties of materials and their structural deterioration, safety factor and reliability, risk evaluation and loads, and their combinations. This book will be of interest to students and professionals in the fields of aerospace, civil, mechanical, marine, and ocean engineering.

Author : Adriano Polpo,Julio Stern,Francisco Louzada,Rafael Izbicki,Hellinton Takada
Publisher : Springer
Page : 304 pages
File Size : 48,7 Mb
Release : 2018-07-12
Category : Mathematics
ISBN : 9783319911434

Get Book

Bayesian Inference and Maximum Entropy Methods in Science and Engineering by Adriano Polpo,Julio Stern,Francisco Louzada,Rafael Izbicki,Hellinton Takada Pdf

These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in São Carlos, Brazil, aim to expand the available research on Bayesian methods and promote their application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications. Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis. For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, including novel techniques and applications, and work that sheds new light on the foundations of inference. Areas of application in these workshops include astronomy and astrophysics, chemistry, communications theory, cosmology, climate studies, earth science, fluid mechanics, genetics, geophysics, machine learning, materials science, medical imaging, nanoscience, source separation, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian computational techniques such as Markov chain Monte Carlo sampling are also regular topics, as are approximate inferential methods. Foundational issues involving probability theory and information theory, as well as novel applications of inference to illuminate the foundations of physical theories, are also of keen interest.

Author : Christian Soize
Publisher : Springer
Page : 329 pages
File Size : 51,7 Mb
Release : 2017-04-24
Category : Computers
ISBN : 9783319543390

Get Book

Uncertainty Quantification by Christian Soize Pdf

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.