![](/images/graphics-bg.png)
Machine Learning of the Reactor Core Loading Pattern Critical Parameters
Joint Authors
Šmuc, Tomislav
Trontl, Krešimir
Pevec, Dubravko
Source
Science and Technology of Nuclear Installations
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2008-08-27
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Engineering Sciences and Information Technology
Abstract EN
The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns.
The speed of the optimization process is highly dependent on the computer code used for the evaluation.
In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation.
We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem.
The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling.
We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.
American Psychological Association (APA)
Trontl, Krešimir& Pevec, Dubravko& Šmuc, Tomislav. 2008. Machine Learning of the Reactor Core Loading Pattern Critical Parameters. Science and Technology of Nuclear Installations،Vol. 2008, no. 2008, pp.1-6.
https://search.emarefa.net/detail/BIM-491248
Modern Language Association (MLA)
Trontl, Krešimir…[et al.]. Machine Learning of the Reactor Core Loading Pattern Critical Parameters. Science and Technology of Nuclear Installations No. 2008 (2008), pp.1-6.
https://search.emarefa.net/detail/BIM-491248
American Medical Association (AMA)
Trontl, Krešimir& Pevec, Dubravko& Šmuc, Tomislav. Machine Learning of the Reactor Core Loading Pattern Critical Parameters. Science and Technology of Nuclear Installations. 2008. Vol. 2008, no. 2008, pp.1-6.
https://search.emarefa.net/detail/BIM-491248
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-491248