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Active learning for support vector regression in radiation shielding design (CROSBI ID 626160)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Dučkić, Paulina ; Trontl, Krešimir ; Matijević, Mario Active learning for support vector regression in radiation shielding design // Proceedings of the 2015 International Conference on High Performance Computing & Simulation (HPCS 2015) / Smari, Waleed W. ; Zeljkovic, Vesna (ur.). Amsterdam: Institute of Electrical and Electronics Engineers (IEEE), 2015. str. 311-317

Podaci o odgovornosti

Dučkić, Paulina ; Trontl, Krešimir ; Matijević, Mario

engleski

Active learning for support vector regression in radiation shielding design

Recently a novel approach based on support vector regression technique has been proposed and tested for the estimation of multi layer buildup factors for gamma ray shielding calculations, while for neutron shielding calculations some initial analyses have been conducted. During the development of the model a number of questions regarding possible application of active learning measures have been raised. In this paper general applicability of the active learning measures on the problem, in particular data transfer method used in the investigation, and testing of the active procedure are discussed.

support vector regression; active learning; data transfer method; point kernel method; gamma buildup factor; neutron buildup factor

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Podaci o prilogu

311-317.

2015.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the 2015 International Conference on High Performance Computing & Simulation (HPCS 2015)

Smari, Waleed W. ; Zeljkovic, Vesna

Amsterdam: Institute of Electrical and Electronics Engineers (IEEE)

978-1-4673-7811-6

Podaci o skupu

International Conference on High Performance Computing & Simulation (HPCS 2015)

predavanje

20.07.2015-24.07.2015

Amsterdam, Nizozemska

Povezanost rada

Elektrotehnika