Browse "Dept. of Nuclear and Quantum Engineering(원자력및양자공학과)" by Author Joung, Semin
Showing results 1 to 14 of 14
| Analysis of Langmuir probe data using artificial neural network Kwon, Daeho; Joung, Semin; Lim, Yegeon; Ghim, Young-chul, KSTAR Conference 2018, National Fusion Research Institute, 2018-02-22 |
| Bayesian based missing input imputation scheme for neural network reconstructing magnetic equilibria in real time Joung, Semin; Kim, Jaewook; Kwak, Sehyun; Park, Kyeo-reh; Jeon, YM; Hahn, SH; Han, HS; et al, 22nd Topical Conference on High Temperature Plasma Diagnostics, American Institute of Physics, 2018-04-19 |
| Bayesian magnetic signal inference from KSTAR for neural network accelerated equilibria reconstruction model Joung, Semin; Kwak, Sehyun; Ghim, Young-chul, KSTAR Conference 2018, National Fusion Research Institute, 2018-02-22 |
| Bayesian neural network for plasma equilibria in the Korea Superconducting Tokamak Advanced Research = KSTAR 플라즈마 평형을 위한 베이즈 추론 신경망link Joung, Semin; Ghim, Young-Chul; et al, 한국과학기술원, 2022 |
| Data-driven Grad-Shafranov solver with KSTAR EFIT data based on neural network and Bayesian inference Joung, Semin; Kim, Jaewook; Kwak, Sehyun; Jeon, YM; Hahn, SH; Han, HS; Kim, HS; et al, 3rd IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis, IAEA, 2019-05-29 |
| Development of machine learning model for automatic ELM-burst detection without hyperparameter adjustment in KSTAR tokamak Song, Jiheon; Joung, Semin; Ghim, Young-Chul; Hahn, Sang-hee; Jang, Juhyeok; Lee, Jungpyo, NUCLEAR ENGINEERING AND TECHNOLOGY, v.55, no.1, pp.100 - 108, 2023-01 |
| GS-DeepNet: mastering tokamak plasma equilibria with deep neural networks and the Grad-Shafranov equation Joung, Semin; Ghim, Young-chul; Kim, Jaewook; Kwak, Sehyun; Kwon, Daeho; Sung, C.; Kim, D.; et al, SCIENTIFIC REPORTS, v.13, no.1, 2023-09 |
| Imputation of faulty magnetic sensors with coupled Bayesian and Gaussian processes to reconstruct the magnetic equilibrium in real time Joung, Semin; Kim, Jaewook; Kwak, Sehyun; Park, Kyeo-Reh; Hahn, S. H.; Han, H. S.; Kim, H. S.; et al, REVIEW OF SCIENTIFIC INSTRUMENTS, v.89, no.10, 2018-10 |
| Neural network based real-time reconstruction of KSTAR magnetic equilibria with Bayesian-based preprocessing Joung, Semin; Kwak, Sehyun; Jeon, Y.M.; Hahn, S.H.; Han, H.S.; Kim, H.S.; Bak, J.G.; et al, 59th Annual Meeting of the APS Division of Plasma Physics, American Physical Society, 2017-10-26 |
| Neural network for real-time plasma equilibrium reconstruction and imputation of missing magnetic signals based on Bayesian analysis in KSTAR Joung, Semin; Kwak, Sehyun; Park, KyeoReh; Ghim, Young-chul, KSTAR Conference 2017, National Fusion Research Institute, 2017-01-19 |
| Neural network magnetic equilibrium reconstruction with Bayesian based preprocessor in KSTAR Joung, Semin; Kwak, Sehyun; Jeon, Y.M.; Hahn, S.H.; Han, H.S.; Kim, H.S.; Bak, J.G.; et al, 11th IAEA Technical Meeting on Control, Data Acquisition, and Remote Participation for Fusion Research, IAEA, 2017-05-09 |
| Non-monotonic radial structures of fluctuating temperatures and densities associated with fishbone activities in KSTAR Lee, Wonjun; Kim, Jaewook; Joung, Semin; Choi, GJ; Kim, J; Woo, M; Rhee, T; et al, PHYSICS OF PLASMAS, v.30, no.2, 2023-02 |
| Real-time compensation of KSTAR magnetic signal drifts based on Bayesian inference Joung, Semin; Kim, H.S.; Ghim, Young-chul, KSTAR Conference 2019, National Fusion Research Institute, 2019-02-21 |
| 인공신경망 기반 실시간 토카막 플라즈마 평형 재구성과 입력 분실 대체를 위한 방법론 제시 = Neural network based real-time Tokamak plasma equilibrium reconstruction and Suggesting methods for missing input imputationlink 정세민; 김영철; et al, 한국과학기술원, 2017 |
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