Abstract/Details

Algorithmic aspects of analysis, prediction, and control in science and engineering: Symmetry-based approach


2012 2012

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Abstract (summary)

Algorithms are extremely important in science and engineering. One of the main objectives of science is to predict future events; this usually requires sophisticated algorithms. Once we are able to predict future events, a natural next step is to influence these events, i.e., to control the corresponding systems; control also usually requires complex algorithms. To be able to predict and control a system, we need to have a good description of this system, so that we can use this description to analyze the system's behavior and extract the desired prediction and control algorithms from this analysis.

A typical prediction is based on the fact that we observed similar situations in the past; we know the outcomes of these past situations, and we expect 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.

Because symmetries are ubiquitous and useful, we will show how symmetries can be used in all classes of algorithmic problems of sciences and engineering: from analysis to prediction to control. Specifically, we show how the symmetry-based approach can be used in the analysis of real-life systems, in the algorithmics of prediction, and in the algorithmics of control.

Indexing (details)


Subject
Computer science
Classification
0984: Computer science
Identifier / keyword
Applied sciences, Control, Extrapolation, Fuzzy logic, Interval computations, Prediction, Symmetry
Title
Algorithmic aspects of analysis, prediction, and control in science and engineering: Symmetry-based approach
Author
Nava, Jaime
Number of pages
225
Publication year
2012
Degree date
2012
School code
0459
Source
DAI-B 74/01(E), Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781267593511
Advisor
Kreinovich, Vladik
Committee member
Ellzey, M. Lawrence; Longpre, Luc
University/institution
The University of Texas at El Paso
Department
Computer Science
University location
United States -- Texas
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3525786
ProQuest document ID
1080790350
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/1080790350
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