Prediction of radionuclide dispersion concentration based on TCN-BiLSTM model
RADIATION PROTECTION|更新时间:2025-12-29
|
Prediction of radionuclide dispersion concentration based on TCN-BiLSTM model
“In the field of nuclear emergency, researchers have proposed a rapid prediction method for nuclide diffusion concentration based on the TCN BiLSTM hybrid neural network model, providing fast and effective support for nuclide diffusion distribution prediction.”
Journal of Radiation Research and Radiation ProcessingVol. 43, Issue 6, Pages: 102-113(2025)
作者机构:
1.淮北师范大学物理与电子工程学院 淮北 235000
2.中国科学院合肥物质科学研究院 合肥 230031
3.中国科学技术大学科学岛分院 合肥 230026
作者简介:
WANG Xiaoxiao (female) was born in September 2000, and obtained a bachelor's degree from Huaibei Normal University in June 2023, and is currently a master's student at the same university, majoring in Electronic Information, E-mail:xxwang@inest.cas.cn
YANG Zihui, associate researcher, E-mail: zihui.yang@inest.cas.cn
基金信息:
the General Project of Anhui Natural Science Foundation(2008085MA23);Director's Fund of Hefei Institutes of Physical Science, CAS(YZJJ202208-TS);The Spent Fuel Reprocessing Research Project
WANG Xiaoxiao, YANG Zihui, AI Yuxing, et al. Prediction of radionuclide dispersion concentration based on TCN-BiLSTM model[J]. Journal of Radiation Research and Radiation Processing, 2025, 43(6): 060601.
WANG Xiaoxiao, YANG Zihui, AI Yuxing, et al. Prediction of radionuclide dispersion concentration based on TCN-BiLSTM model[J]. Journal of Radiation Research and Radiation Processing, 2025, 43(6): 060601. DOI: 10.11889/j.1000-3436.2025-0057. CSTR: 32195.14.j.JRRRP.1000-3436.2025-0057.
Prediction of radionuclide dispersion concentration based on TCN-BiLSTM model