Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Science & Nature, Technology, Engineering, General Computing
Cover of the book Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications by Andrew Pownuk, Vladik Kreinovich, Springer International Publishing
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Author: Andrew Pownuk, Vladik Kreinovich ISBN: 9783319910260
Publisher: Springer International Publishing Publication: May 3, 2018
Imprint: Springer Language: English
Author: Andrew Pownuk, Vladik Kreinovich
ISBN: 9783319910260
Publisher: Springer International Publishing
Publication: May 3, 2018
Imprint: Springer
Language: English

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. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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. 

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