Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications (Hardcover, 1st ed. 2018)

How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors' objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 773
Release date:	May 2018
First published:	2018
Authors:	Andrew Pownuk • Vladik Kreinovich
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	202
Edition:	1st ed. 2018
ISBN-13:	978-3-319-91025-3
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-91025-6
Barcode:	9783319910253

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