| Deep neural network model with Bayesian hyperparameter optimization for prediction of NOx at transient conditions in a diesel engine S Shin, Y Lee, M Kim, J Park, S Lee, K Min Engineering Applications of Artificial Intelligence 94, 103761, 2020 | 94 | 2020 |
| Prediction modeling and analysis of knocking combustion using an improved 0D RGF model and supervised deep learning S Cho, J Park, C Song, S Oh, S Lee, M Kim, K Min Energies 12 (5), 844, 2019 | 28 | 2019 |
| Deep learning procedure for knock, performance and emission prediction at steady-state condition of a gasoline engine S Shin, S Lee, M Kim, J Park, K Min Proceedings of the Institution of Mechanical Engineers, Part D: Journal of …, 2020 | 25 | 2020 |
| Predicting transient diesel engine NOx emissions using time-series data preprocessing with deep-learning models S Shin, Y Lee, J Park, M Kim, S Lee, K Min Proceedings of the Institution of Mechanical Engineers, Part D: Journal of …, 2021 | 15 | 2021 |
| Prediction of engine NOx for virtual sensor using deep neural network and genetic algorithm J Kim, J Park, S Shin, Y Lee, K Min, S Lee, M Kim Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles 76, 72, 2021 | 13 | 2021 |
| EGR prediction of diesel engines in steady-state conditions using deep learning method S Lee, Y Lee, Y Lee, M Kim, S Shin, J Park, K Min International Journal of Automotive Technology 21, 571-578, 2020 | 12 | 2020 |
| Designing a steady-state experimental dataset for predicting transient NOx emissions of diesel engines via deep learning S Shin, Y Lee, Y Lee, J Park, M Kim, S Lee, K Min Expert Systems with Applications 198, 116919, 2022 | 10 | 2022 |
| Comparative study on the prediction of city bus speed between LSTM and GRU G Hwang, Y Hwang, S Shin, J Park, S Lee, M Kim International journal of automotive technology 23 (4), 983-992, 2022 | 6 | 2022 |
| Proposal of a methodology for designing engine operating variables using predicted NOx emissions based on deep neural networks S Lee, Y Lee, Y Lee, S Shin, M Kim, J Park, K Min Journal of Mechanical Science and Technology 35, 1747-1756, 2021 | 5 | 2021 |
| Improvement of knock onset determination based on supervised deep learning using data filtering J Park, S Lee, S Cho, S Shin, M Kim, C Song, K Min SAE Technical Paper, 2021 | 2 | 2021 |
| Prediction of hybrid electric bus speed using deep learning method G Hwang, S Lee, K Min, J Park, S Shin, J Kim, H Nguyen, Y Hwang, ... SAE Technical Paper, 2020 | 2 | 2020 |
| Development of a Light and Accurate Nox Prediction Model for Diesel Engines Using Machine Learning and Xai Methods JJ Park, S Lee, S Shin, M Kim, J Park International Journal of Automotive Technology 24 (2), 559-571, 2023 | 1 | 2023 |
| 딥러닝을 활용한 실차 실험 기반 공기 압축기 모터 온도 예측 김현욱， 임동현， 박지환， 김지웅， 민경덕 한국자동차공학회 추계학술대회 및 전시회, 1532-1536, 2023 | | 2023 |
| Knock Onset Determination with 1D CNN Using Random Search Hyperparameter Optimization and Data Augmentation in SI Engine J Park, S Shin, S Oh, S Lee, W Shin, K Min International Journal of Automotive Technology 24 (5), 1395-1410, 2023 | | 2023 |
| Task Transfer Learning for Prediction of Transient Nitrogen Oxides, Soot, and Total Hydrocarbon Emissions of a Diesel Engine S Shin, M Kim, J Park, S Lee, K Min IEEE Access, 2023 | | 2023 |
| Mass Burned Prediction with 1-dimensional Convolutional Neural Networks for Predicting Knock Probability P Jihwan, S Seunghyup, L Sangyul, K Minjae, C Seungmok, I Hyuk, ... SAE Energy & Propulsion Conference & Exhibition, 2023 | | 2023 |
| 연소압 센서 및 딥러닝 점화 지연 예측 모델 기반 노킹 발생 확률 예측 박지환， 신승협， 이상열， 김민재， 최승목， 임혁， 민경덕 한국자동차공학회 춘계학술대회, 59-59, 2022 | | 2022 |
| 딥러닝을 이용한 노킹 센서 기반 노킹 강도 예측 모델 개발 박지환， 신승협， 이상열， 김민재， 이승현， 정인수， 민경덕 한국자동차공학회 추계학술대회 및 전시회, 51-51, 2021 | | 2021 |
| 시계열 딥러닝을 적용한 직렬형 하이브리드 자동차의 에너지 관리 전략에 관한 연구 황영하， 황기연， 응오， 테남， 도쫑뚜， 박지환， 신승협， 민경덕， 이상열， ... 한국자동차공학회 춘계학술대회, 741-741, 2021 | | 2021 |
| 하이브리드 버스 에너지 관리 전략을 위한 속도 예측 황기연， 황영하， 신승협， 박지환， 민경덕， 이상열， 김종명， 김민재 한국자동차공학회 춘계학술대회, 829-829, 2020 | | 2020 |
