How Uncertainty-Related Ideas Can Provide Theoretical Explanation For Empirical Dependencies (Paperback, 1st ed. 2021)

This book shows how to provide uncertainty-related theoretical justification for empirical dependencies, on the examples from numerous application areas. Such justifications are needed, since without them, practitioners may be reluctant to use these dependencies: purely empirical formulas often turn out to hold only in some cases. Examples of new theoretical explanations range from fundamental physics (quark confinement, galaxy superclusters, etc.) and geophysics (earthquake analysis) to transportation and electrical engineering to computer science (image processing, quantum computing) and pedagogy (equity, effect of repetitions). The book is useful to students and specialists in the corresponding areas. Most of the examples use common general techniques, so the book is also useful to practitioners and researchers in other application areas who look for ways to provide theoretical justifications for their areas' empirical dependencies.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Systems, Decision and Control, 306
Release date:	March 2022
First published:	2021
Editors:	Martine Ceberio • Vladik Kreinovich
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	151
Edition:	1st ed. 2021
ISBN-13:	978-3-03-065326-2
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-065326-9
Barcode:	9783030653262

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