Active learning for support vector regression in radiation shielding design (CROSBI ID 626160)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
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
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
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