PDF [DOWNLOAD] Fundamentals of Uncertainty

Fundamentals of Uncertainty Quantification for Engineers: Methods and Models by Yan Wang Ph.D, Anh.V. Tran Ph.D., David L. Mcdowell Ph.D.

• Fundamentals of Uncertainty Quantification for Engineers: Methods and Models
• Yan Wang Ph.D, Anh.V. Tran Ph.D., David L. Mcdowell Ph.D.
• Page: 434
• Format: pdf, ePub, mobi, fb2
• ISBN: 9780443136610
• Publisher: Elsevier Science

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Books downloadable to kindle Fundamentals of Uncertainty Quantification for Engineers: Methods and Models English version FB2 DJVU PDB by Yan Wang Ph.D, Anh.V. Tran Ph.D., David L. Mcdowell Ph.D. 9780443136610

Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) accompanied by a wide variety of applied examples and implementation details to reinforce the concepts outlined in the book. Sections start with an introduction to the history of probability theory and an overview of recent developments of UQ methods in the domains of applied mathematics and data science. Major concepts of copula, Monte Carlo sampling, Markov chain Monte Carlo, polynomial regression, Gaussian process regression, polynomial chaos expansion, stochastic collocation, Bayesian inference, modelform uncertainty, multi-fidelity modeling, model validation, local and global sensitivity analyses, linear and nonlinear dimensionality reduction are included. Advanced UQ methods are also introduced, including stochastic processes, stochastic differential equations, random fields, fractional stochastic differential equations, hidden Markov model, linear Gaussian state space model, as well as non-probabilistic methods such as robust Bayesian analysis, Dempster-Shafer theory, imprecise probability, and interval probability. The book also includes example applications in multiscale modeling, reliability, fatigue, materials design, machine learning, and decision making.

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Fundamentals of Uncertainty Quantification for Engineers
Fundamentals of Uncertainty Quantification for Engineers: Methods and Models provides a comprehensive introduction to uncertainty quantification (UQ) .
Fundamentals of Uncertainty Quantification for Engineers: Methods .
The book also includes example applications in multiscale modeling, reliability, fatigue, materials design, machine learning, and decision making.

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