UID:
almahu_9948654387302882
Format:
VI, 573 p. 155 illus., 108 illus. in color.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030601669
Content:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030601652
Additional Edition:
Printed edition: ISBN 9783030601676
Additional Edition:
Printed edition: ISBN 9783030601683
Language:
English
DOI:
10.1007/978-3-030-60166-9
URL:
https://doi.org/10.1007/978-3-030-60166-9
