Machine learning-enabled weather forecasting for real-time radioactive transport and contamination prediction-Reference-Cited by-同舟云学术

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Machine learning-enabled weather forecasting for real-time radioactive transport and contamination prediction

Published:2024-08 Issue: Volume:173 Page:105255
ISSN:0149-1970
Container-title:Progress in Nuclear Energy
language:en
Short-container-title:Progress in Nuclear Energy

Author:

Ayoub Ali^ORCID,Wainwright Haruko M.,Sansavini Giovanni

Publisher

Elsevier BV

Reference40 articles.

1. Comparison of ARIMA and artificial neural networks models for stock price prediction;Adebiyi;J. Appl. Math.,2014

2. Constructing a web service system for large-scale meteorological grid data;Amagasa,2007

3. Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential;Amato;Stoch. Environ. Res. Risk Assess.,2022

4. The power of precursors: an empirical assessment of nuclear power risks;Ayoub;Prog. Nucl. Energy,2023

5. Resilient design in nuclear energy: critical lessons from a cross-disciplinary review of the Fukushima dai-ichi nuclear accident;Ayoub;iScience,2024

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. An enhanced fourier neural operator surrogate for radioactive plume transport forecasting;Stochastic Environmental Research and Risk Assessment;2024-05-16

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