About this book
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.
Computational Intelligence Interval Uncertainty Uncertainty Probabilistic Uncertainty Fuzziness
- Book Title Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
- Series Title Studies in Computational Intelligence
- Series Abbreviated Title Studies Comp.Intelligence
- DOI https://doi.org/10.1007/978-3-319-91026-0
- Copyright Information Springer International Publishing AG, part of Springer Nature 2018
- Publisher Name Springer, Cham
- eBook Packages Engineering Engineering (R0)
- Hardcover ISBN 978-3-319-91025-3
- Softcover ISBN 978-3-030-08158-4
- eBook ISBN 978-3-319-91026-0
- Series ISSN 1860-949X
- Series E-ISSN 1860-9503
- Edition Number 1
- Number of Pages XI, 202
- Number of Illustrations 1 b/w illustrations, 1 illustrations in colour
- Buy this book on publisher's site
“The book is well structured and easy to work through. Without confusing detours, the authors always come directly to the point, clearly explaining what they are doing and why.” (Heinrich Hering, zbMATH 1432.93003, 2020)