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Optimization Under Uncertainty with Applications to Aerospace Engineering (Hardcover, 1st ed. 2021) Loot Price: R4,707
Discovery Miles 47 070
Optimization Under Uncertainty with Applications to Aerospace Engineering (Hardcover, 1st ed. 2021): Massimiliano Vasile

Optimization Under Uncertainty with Applications to Aerospace Engineering (Hardcover, 1st ed. 2021)

Massimiliano Vasile

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Loot Price R4,707 Discovery Miles 47 070 | Repayment Terms: R441 pm x 12*

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In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Release date: February 2021
First published: 2021
Editors: Massimiliano Vasile
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 573
Edition: 1st ed. 2021
ISBN-13: 978-3-03-060165-2
Categories: Books > Science & Mathematics > Astronomy, space & time > General
Books > Science & Mathematics > Mathematics > Optimization > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General
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LSN: 3-03-060165-X
Barcode: 9783030601652

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