Artificial neural networks for NAA: proof of concept on data analysed with k0-based software-Reference-Cited by-同舟云学术

Artificial neural networks for NAA: proof of concept on data analysed with k0-based software

Published:2022-10-01 Issue: Volume: Page:
ISSN:0236-5731
Container-title:Journal of Radioanalytical and Nuclear Chemistry
language:en
Short-container-title:J Radioanal Nucl Chem

Author:

Barradas N. Pessoa^ORCID,Farjallah N.,Vieira A.,Blaauw M.

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health,Spectroscopy,Pollution,Radiology, Nuclear Medicine and imaging,Nuclear Energy and Engineering,Analytical Chemistry

Link

https://link.springer.com/content/pdf/10.1007/s10967-022-08568-8.pdf

Reference36 articles.

1. International Atomic Energy Agency (2022) Research reactor database. https://nucleus.iaea.org/rrdb/#/home

2. International Atomic Energy Agency (2018) Proficiency testing by interlaboratory comparison performed in 2010–2015 for neutron activation analysis and other analytical techniques. IAEA-TECDOC-1831, IAEA, Vienna

3. International Atomic Energy Agency (2018) Development of an integrated approach to routine automation of neutron activation analysis. IAEA-TECDOC-1839, IAEA, Vienna

4. International Atomic Energy Agency (2018) Advances in neutron activation analysis of large objects with emphasis on archaeological examples results of a coordinated research project. IAEA-TECDOC-1838, IAEA, Vienna

5. International Atomic Energy Agency (2022) Quality assurance and quality control in neutron activation analysis: a guide to practical approaches. IAEA technical reports series 487, IAEA, Vienna

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting element concentrations by machine learning models in neutron activation analysis;Journal of Radioanalytical and Nuclear Chemistry;2024-03-07