Algorithmic Aspects of Analysis, Predictio...

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Sprache: Englisch

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Beschreibung

This book demonstrates how to describe and analyze a system's behavior and extract the desired prediction and control algorithms from this analysis. A typical prediction is based on observing similar situations in the past, knowing the outcomes of these past situations, and expecting that the future outcome of the current situation will be similar to these past observed outcomes. In mathematical terms, similarity corresponds to symmetry, and similarity of outcomes to invariance.

This book shows how symmetries can be used in all classes of algorithmic problems of sciences and engineering: from analysis to prediction to control. Applications cover chemistry, geosciences, intelligent control, neural networks, quantum physics, and thermal physics. Specifically, it is shown how the approach based on symmetry and similarity can be used in the analysis of real-life systems, in the algorithms of prediction, and in the algorithms of control.

Inhaltsverzeichnis

Introduction: Symmetries and Similarities as a Methodology for Algorithmics of Analysis, Prediction, and Control in Science and Engineering.- Algorithmic Aspects of Real-Life Systems Analysis: Approach Based on Symmetry and Simila.- Algorithmic Aspects of Prediction: An Approach Based on Symmetry and Similarity.- Algorithmic Aspects of Control: Approach Based on Symmetry and Similarity.- Possible Ideas for FutureWork.

Erscheinungsjahr:	2014
Fachbereich:	EDV
Genre:	Informatik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Inhalt:	viii 155 S. 8 s/w Illustr. 155 p. 8 illus.
ISBN-13:	9783662449547
ISBN-10:	3662449544
Sprache:	Englisch
Autor:	Nava, Jaime Kreinovich, Vladik
Hersteller:	Springer Springer, Berlin Springer Berlin Heidelberg
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Abbildungen:	VIII, 155 p. 8 illus.
Maße:	242 x 162 x 11 mm
Von/Mit:	Jaime Nava (u. a.)
Erscheinungsdatum:	04.11.2014
Gewicht:	0,362 kg