Overview
- Presents how symmetries can be used in all classes of algorithmic problems of sciences and engineering
- Shows how the symmetry-based approach can be used in the analysis of real-life systems, from prediction to control
- Written by leading experts in the field
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 14)
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Table of contents (5 chapters)
Keywords
About this book
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. Â
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.
Authors and Affiliations
Bibliographic Information
Book Title: Algorithmic Aspects of Analysis, Prediction, and Control in Science and Engineering
Book Subtitle: An Approach Based on Symmetry and Similarity
Authors: Jaime Nava, Vladik Kreinovich
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-662-44955-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-44954-7Published: 04 November 2014
Softcover ISBN: 978-3-662-51159-6Published: 22 September 2016
eBook ISBN: 978-3-662-44955-4Published: 18 October 2014
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: VIII, 155
Number of Illustrations: 8 b/w illustrations
Topics: Computational Intelligence, Artificial Intelligence, Control and Systems Theory
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