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Pregled bibliografske jedinice broj: 309974

Support vector regression model for the estimation of γ -ray buildup factors for multi-layer shields


Trontl, Krešimir; Šmuc, Tomislav; Pevec, Dubravko
Support vector regression model for the estimation of γ -ray buildup factors for multi-layer shields // Annals of Nuclear Energy, 34 (2007), 12; 939-952 (međunarodna recenzija, članak, znanstveni)


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Naslov
Support vector regression model for the estimation of γ -ray buildup factors for multi-layer shields

Autori
Trontl, Krešimir ; Šmuc, Tomislav ; Pevec, Dubravko

Izvornik
Annals of Nuclear Energy (0306-4549) 34 (2007), 12; 939-952

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
support vector regression (SVR); buildup factor; point-kernel method; dose radiation

Sažetak
The accuracy of the point-kernel method, which is a widely used practical tool for γ -ray shielding calculations, strongly depends on the quality and accuracy of buildup factors used in the calculations. Although, buildup factors for single-layer shields comprised of a single material are well known, calculation of buildup factors for stratified shields, each layer comprised of different material or a combination of materials, represent a complex physical problem. Recently, a new compact mathematical model for multi-layer shield buildup factor representation has been suggested for embedding into point-kernel codes thus replacing traditionally generated complex mathematical expressions. The new regression model is based on support vector machines learning technique, which is an extension of Statistical Learning Theory. The paper gives complete description of the novel methodology with results pertaining to realistic engineering multi-layer shielding geometries. The results based on support vector regression machine learning confirm that this approach provides a framework for general, accurate and computationally acceptable multi-layer buildup factor model.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo



POVEZANOST RADA


Projekt / tema
036-0361590-1579 - Gospodarenje gorivom standardnih i naprednih nuklearnih reaktora (Dubravko Pevec, )
098-0982560-2565 - Postupci računalne inteligencije u mjernim sustavima (Ivan Marić, )

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb,
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Dubravko Pevec (autor)

Avatar Url Tomislav Šmuc (autor)

Avatar Url Krešimir Trontl (autor)

Citiraj ovu publikaciju

Trontl, Krešimir; Šmuc, Tomislav; Pevec, Dubravko
Support vector regression model for the estimation of γ -ray buildup factors for multi-layer shields // Annals of Nuclear Energy, 34 (2007), 12; 939-952 (međunarodna recenzija, članak, znanstveni)
Trontl, K., Šmuc, T. & Pevec, D. (2007) Support vector regression model for the estimation of γ -ray buildup factors for multi-layer shields. Annals of Nuclear Energy, 34 (12), 939-952.
@article{article, year = {2007}, pages = {939-952}, keywords = {support vector regression (SVR), buildup factor, point-kernel method, dose radiation}, journal = {Annals of Nuclear Energy}, volume = {34}, number = {12}, issn = {0306-4549}, title = {Support vector regression model for the estimation of and \#947; -ray buildup factors for multi-layer shields}, keyword = {support vector regression (SVR), buildup factor, point-kernel method, dose radiation} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus