Linear Regression and Machine Learning for Nuclear Forensics of Spent Fuel from Six Types of Nuclear Reactors-Reference-Cited by-同舟云学术

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Linear Regression and Machine Learning for Nuclear Forensics of Spent Fuel from Six Types of Nuclear Reactors

Published:2023-03-09 Issue:3 Volume:19 Page:
ISSN:2331-7019
Container-title:Physical Review Applied
language:en
Short-container-title:Phys. Rev. Applied

Author:

Chen Shengli^ORCID,Wang Tianxiang,Zhang Zhong^ORCID,Li Runfeng,Yuan Su,Zhang Ruiyi,Yuan Cenxi^ORCID,Zhang Chunyu,Zhu Jianyu

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Sun Yat-sen University

Guangdong Major Project of Basic and Applied Basic Research

International Sci & Tech Cooperation Program of Guangdong

Fundamental Major Sci & Tech Special Project of Guangdong

Publisher

American Physical Society (APS)

Subject

General Physics and Astronomy

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevApplied.19.034028/fulltext

Reference32 articles.

1. Sensitivity of Seismically Cued Antineutrino Detectors to Nuclear Explosions

2. 233U/236U signature allows to distinguish environmental emissions of civil nuclear industry from weapons fallout

3. Non-natural ruthenium isotope ratios of the undeclared 2017 atmospheric release consistent with civilian nuclear activities

4. Rapid imaging of special nuclear materials for nuclear nonproliferation and terrorism prevention

5. Nuclear forensics—a methodology providing clues on the origin of illicitly trafficked nuclear materials

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1. A once-through artificial neural network approach for used nuclear fuel inverse depletion analysis: A comparative study;Annals of Nuclear Energy;2024-09

2. Multi-objective optimization of molten salt microreactor shielding perturbations employing machine learning;Nuclear Engineering and Design;2024-09

3. Calculating α -decay half-lives with artificial neural networks considering the effects of angular momentum and deformation;Physical Review C;2024-08-20

4. Optimization of passive modular molten salt microreactor geometric perturbations using machine learning;Nuclear Engineering and Design;2024-08

5. Towards inferring reactor operations from high-level waste;Nuclear Engineering and Technology;2024-07

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