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Algorithmic aspects of analysis, prediction, and control in science and engineering = an approach based on symmetry and similarity /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Algorithmic aspects of analysis, prediction, and control in science and engineering/ by Jaime Nava, Vladik Kreinovich.
Reminder of title:	an approach based on symmetry and similarity /
Author:	Nava, Jaime.
other author:	Kreinovich, Vladik.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	viii, 155 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Computer algorithms. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-44955-4
ISBN:	9783662449554 (electronic bk.)

Algorithmic aspects of analysis, prediction, and control in science and engineering = an approach based on symmetry and similarity /
Nava, Jaime.

Algorithmic aspects of analysis, prediction, and control in science and engineeringan approach based on symmetry and similarity /[electronic resource] :by Jaime Nava, Vladik Kreinovich. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - viii, 155 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.142198-4182 ;. - Studies in systems, decision and control ;v. 2. .

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.

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.

ISBN: 9783662449554 (electronic bk.)

Standard No.: 10.1007/978-3-662-44955-4doiSubjects--Topical Terms:

528448
Computer algorithms.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.1

Algorithmic aspects of analysis, prediction, and control in science and engineering = an approach based on symmetry and similarity /
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245 1 0 $a Algorithmic aspects of analysis, prediction, and control in science and engineering $h [electronic resource] : $b an approach based on symmetry and similarity / $c by Jaime Nava, Vladik Kreinovich.
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300 $a viii, 155 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4182 ; $v v.14
505 0 $a 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.
520 $a 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.
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