| Real-time prediction of nuclear power plant parameter trends following operator actions J Bae, G Kim, SJ Lee Expert Systems with Applications 186, 115848, 2021 | 41 | 2021 |
| Comparison of multilayer perceptron and long short-term memory for plant parameter trend prediction J Bae, J Ahn, SJ Lee Nuclear Technology 206 (7), 951-961, 2020 | 16 | 2020 |
| An interpretable convolutional neural network for nuclear power plant abnormal events JH Shin, J Bae, JM Kim, SJ Lee Applied Soft Computing 132, 109792, 2023 | 9 | 2023 |
| Limit surface/states searching algorithm with a deep neural network and Monte Carlo dropout for nuclear power plant safety assessment J Bae, JW Park, SJ Lee Applied Soft Computing 124, 109007, 2022 | 8 | 2022 |
| Operation validation system to prevent human errors in nuclear power plants J Ahn, J Bae, BJ Min, SJ Lee Nuclear Engineering and Design 397, 111949, 2022 | 7 | 2022 |
| A human error detection system in nuclear power plant operations J Ahn, J Bae, SJ Lee American Nuclear Society, 2019 | 7 | 2019 |
| Deep reinforcement learning for a multi-objective operation in a nuclear power plant J Bae, JM Kim, SJ Lee Nuclear Engineering and Technology 55 (9), 3277-3290, 2023 | 5 | 2023 |
| Strategy to coordinate actions through a plant parameter prediction model during startup operation of a nuclear power plant JM Kim, J Bae, SJ Lee Nuclear Engineering and Technology 55 (3), 839-849, 2023 | 3 | 2023 |
| An Autonomous Pressure Controller based on Approximation of Action Value Function J Bae, J Kim, SJ Lee Transactions of the Korean Nuclear Society, 2020 | 3 | 2020 |
| Framework for operator manipulation validation system using plant parameter prediction J Bae, SJ Lee Korean nuclear society autumn meeting, Korean Nuclear Society, 2019 | 3 | 2019 |
| Deep-learning for Guided Simulation of Scenarios for Dynamic Probabilistic Risk Assessment J Bae, JW Park, SJ Lee PSAM, 2022 | 1 | 2022 |
| Uncertainty-aware Limit Surface Search Algorithm using Deep Neural Network J Bae, SJ Lee ANS, 2021 | 1 | 2021 |
| Limit Surface Search Algorithm With Artificial Neural Network and Monte Carlo Dropout Uncertainty Quantification J Bae, SJ Lee PSA, 2021 | 1 | 2021 |
| Nuclear Power Plant Parameter Prediction Strategy for Human Error Detection J Bae, SJ Lee America Nuclear Society, 2019 | 1 | 2019 |
| Application of reinforcement learning to deduce nuclear power plant severe accident scenario SH Song, Y Lee, JY Bae, KS Song, MR Seo, SJ Kim, JI Lee Annals of Nuclear Energy 205, 110605, 2024 | | 2024 |
| Success Criteria Analysis using Deep Neural Network and Monte Carlo Dropout for Dynamic Probabilistic Safety Assessment Y Heo, J Bae, W Jo, SJ Lee | | 2023 |
| Adaptive Sampling for Limit Surface Search using Deep Neural Network and Monte Carlo Dropout J Bae, SJ Lee 한국원자력학회, 2021 | | 2021 |
| Development of Evaluation Method for Startup Operation of Nuclear Power Plants J Kim, SJ Lee 한국원자력학회, 2021 | | 2021 |
| Adaptive Sampling of Dynamic Scenarios close to the Limit Surface using Deep Neural Network and Monte Carlo Dropout J Bae, JW Park, SJ Lee | | 2021 |
| Application of Artificial Neural Network for Plant Parameter Forecasting J Bae, SJ Lee America Nuclear Society, 2019 | | 2019 |
Jae Min KimKorea Atomic Energy Research Institute (KAERI)Verified email at kaeri.re.kr
