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Showing results 137381 to 137400 of 275773
| 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 forecasting of stock price index to integrate change-point detection with genetic algorithms Kim, Kyoung-jae; Oh, Kyong Joo; Han, Ingoo, The Korea Society of Management Information Systems, Fall 2000, pp.141 - 150, The Korea Society of Management Information Systems, 2000 |
| Neural Network Forecasting Using Data Mining Classifiers Based on Structural Change: Application to Stock Price Index Kyong Joo Oh; In Goo Han, 한국통계학회 논문집, v.8, no.2, pp.543 - 556, 2001-08 |
| Neural Network Forecasting Using Data Mining Classifiers Based on Structural Change: Application to Stock Price Index Oh, Kyong Joo; Han, Ingoo, The Korean Communications in Statistics, Vol. 8, No. 2, 2001, pp. 543-556(14), 2001 |
| Neural Network Guidance Based on Pursuit-Evasion Games with Enhanced Performance Choi, Han-Lim; Bang, Hyochoong; Tahk, Min-Jea, 15th IFAC World Congress, 2002-07 |
| Neural network guidance based on pursuit-evasion games with enhanced performance Choi, Han-Lim; Tahk, Min-Jea; Bang, Hyochoong, Control Engineering Practice, Vol.14, pp.735-742, 2006 |
| Neural network guidance based on pursuit-evasion games with enhanced performance Choi, Han-Lim; Tahk, Min-Jea; Bang, Hyochoong, CONTROL ENGINEERING PRACTICE, v.14, no.7, pp.735 - 742, 2006-07 |
| Neural network Hamiltonian: development of tight-binding-based Hamiltonian generation simulator for crystal structure = 인공 신경망 해밀토니안: 결정 구조에 대한 tight-binding 방법 기반 해밀토니안 생성 시뮬레이터 개발link Choi, Geunseok; Shin, Mincheol; et al, 한국과학기술원, 2022 |
| Neural Network Identification and Control of Unstable Systems Using Supervisory Control While Leraning Kim, Sung-Woo; Hong, Sun-Gi; Ohm, Tae-Duck; Lee, Ju-Jang, the 1994 IEEE International Conference on Neural Networks, pp.2500 - 2505, IEEE, 1994-06-27 |
| Neural network learning and control of uncertain robot systems with guaranteed stability = 불확실한 로봇 시스템의 안정성을 보장하는 신경회로망의 학습 및 제어link Kim, Sung-Woo; 김성우; et al, 한국과학기술원, 1996 |
| NEURAL NETWORK LEARNING METHOD AND DEVICE FOR RECOGNIZING CLASS Kim, Junmo; Kim, Byung-ju; Kim, Joo-chang; Lee, Ye-gang; Park, Min-seok; Yun, Ju-seung; Lee, Jae-young; et al |
| Neural Network Learning using Time-Varying Two-Phase Optimization Myung, Hyun; Kim, Jong-Hwan, The 33rd IEEE Conference on Decision and Control. Part 1 (of 4), pp.1881 - 1882, ., 1994-12-14 |
| 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 |
| Neural network magnetic equilibrium reconstruction with Bayesian based preprocessor in KSTAR 정세민; 곽세현; 박겨레; 김영철, 한국물리학회 춘계학술대회, 한국물리학회, 2017-04-19 |
| Neural network method and apparatus Kim, Lee-Sup; Lee, Sehwan; Sim, Jaehyeong; Kim, Hyeonuk; Choi, Yeongjae |
| Neural network method and apparatus Kim, Lee-Sup; Kim, Hyeonuk; Sim, Jaehyeong; Choi, Yeongjae; Lee, Sehwan |
| NEURAL NETWORK MODEL FOR ESTIMATING DEPARTURE FROM NUCLEATE BOILING PERFORMANCE OF A PRESSURIZED WATER-REACTOR CORE KIM, HK; LEE, SH; Chang, Soon-Heung, NUCLEAR TECHNOLOGY, v.101, no.2, pp.111 - 122, 1993-02 |
| Neural Network Model with Fixed Global Interconnects and Adaptive Bit-Significance B.Y.Koh; H.J.Lee; S.Y.Lee, 전자공학회논문지, v.28, no.2, pp.61 - 69, 1991 |
| Neural network modeling for rainfall prediction: observation extrapolation and numerical forecast correction = 강우 예측 신경망 모델링: 관측 외삽과 수치 예보 보정link Jeong, Chang-Hoo; Yi, Mun Yong; et al, 한국과학기술원, 2022 |
| Neural Network Modeling supported by Change-Point Detection for the Prediction of the U.S. Treasury Securities Oh, Kyong Joo; Han, Ingoo, the Korean Operations Research and Management Science Society, no.2, pp.37 - 39, The Korean Operations Research and Management Science Society, 2000 |
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