EPJ Web Conf.
Volume 247, 2021PHYSOR2020 – International Conference on Physics of Reactors: Transition to a Scalable Nuclear Future
|Number of page(s)||8|
|Section||Sensitivity & Uncertainty Methods|
|Published online||22 February 2021|
- Y. LeCun, Y. Bengio, and G. Hinton. “Deep learning.” nature, volume 521(7553), p. 436 (2015). [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- R. S. Sutton and A. G. Barto. Reinforcement learning: An introduction. MIT press (2018). [Google Scholar]
- M. I. Radaideh and T. Kozlowski. “Combining simulations and data with deep learning and uncertainty quantification for advanced energy modeling.” International Journal of Energy Research, volume in press (2019). [PubMed] [Google Scholar]
- M. I. Radaideh and T. Kozlowski. “Analyzing nuclear reactor simulation data and uncertainty with the Group Method of Data Handling.” Nuclear Engineering and Technology, volume in press (2019). [Google Scholar]
- Y. Liu, N. Dinh, Y. Sato, and B. Niceno. “Data-driven modeling for boiling heat transfer: using deep neural networks and high-fidelity simulation results.” Applied Thermal Engineering, volume 144, pp. 305–320 (2018). [Google Scholar]
- J. Yang and J. Kim. “An accident diagnosis algorithm using long short-term memory.” Nuclear Engineering and Technology, volume 50(4), pp. 582–588 (2018). [Google Scholar]
- P. Grechanuk, M. E. Rising, and T. S. Palmer. “Using Machine Learning Methods to Predict Bias in Nuclear Criticality Safety.” Journal of Computational and Theoretical Transport, volume 47(4-6), pp. 552–565 (2018). [Google Scholar]
- S. M. Bowman. “SCALE 6: comprehensive nuclear safety analysis code system.” Nuclear technology, volume 174(2), pp. 126–148 (2011). [Google Scholar]
- F. Chollet. “Keras: Deep learning library for theano and tensorflow.” http://kerasio (2015). [Google Scholar]
- A. B. Owen. “Sobol’indices and Shapley value.” SIAM/ASA Journal on Uncertainty Quantification, volume 2(1), pp. 245–251 (2014). [Google Scholar]
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