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How Uncertainty-Related Ideas Can Provide Theoretical Explanation For Empirical Dependencies. 2021 ed.

How Uncertainty-Related Ideas Can Provide Theoretical Explanation For Empirical Dependencies. 2021 ed.

・ISBN 978-3-030-65326-2 paper EUR 159.99

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お気に入り
著者・編者Ceberio, Martine / Kreinovich, Vladik (eds.),
シリーズ (Studies in Systems, Decision and Control)
出版社 (Springer Nature Switzerland AG, SZ)
出版年月2022
ページ数151 pp.
言語ENG
ニュース番号<A03-93597>

解説

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.