| Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management R Lu, YC Li, Y Li, J Jiang, Y Ding Applied Energy 276, 115473, 2020 | 151 | 2020 |
| Demand response management for industrial facilities: A deep reinforcement learning approach X Huang, SH Hong, M Yu, Y Ding, J Jiang IEEE Access 7, 82194-82205, 2019 | 87 | 2019 |
| Data-driven real-time price-based demand response for industrial facilities energy management R Lu, R Bai, Y Huang, Y Li, J Jiang, Y Ding Applied Energy 283, 116291, 2021 | 80 | 2021 |
| Toward the plug-and-produce capability for industry 4.0: An asset administration shell approach X Ye, J Jiang, C Lee, N Kim, M Yu, SH Hong IEEE Industrial Electronics Magazine 14 (4), 146-157, 2020 | 68 | 2020 |
| Deep reinforcement learning-based demand response for smart facilities energy management R Lu, R Bai, Z Luo, J Jiang, M Sun, HT Zhang IEEE Transactions on Industrial Electronics 69 (8), 8554-8565, 2021 | 63 | 2021 |
| A time-sensitive networking (TSN) simulation model based on OMNET++ J Jiang, Y Li, SH Hong, A Xu, K Wang 2018 IEEE International Conference on Mechatronics and Automation (ICMA …, 2018 | 57 | 2018 |
| Practical implementation of an OPC UA TSN communication architecture for a manufacturing system Y Li, J Jiang, C Lee, SH Hong IEEE Access 8, 200100-200111, 2020 | 50 | 2020 |
| A hybrid deep learning-based online energy management scheme for industrial microgrid R Lu, R Bai, Y Ding, M Wei, J Jiang, M Sun, F Xiao, HT Zhang Applied Energy 304, 117857, 2021 | 42 | 2021 |
| Testbed implementation of reinforcement learning-based demand response energy management system X Zhang, R Lu, J Jiang, SH Hong, WS Song Applied energy 297, 117131, 2021 | 37 | 2021 |
| A simulation model for time-sensitive networking (TSN) with experimental validation J Jiang, Y Li, SH Hong, M Yu, A Xu, M Wei 2019 24th IEEE International Conference on Emerging Technologies and Factory …, 2019 | 32 | 2019 |
| Joint traffic routing and scheduling algorithm eliminating the nondeterministic interruption for TSN networks used in IIoT Y Li, J Jiang, SH Hong IEEE Internet of Things Journal 9 (19), 18663-18680, 2022 | 19 | 2022 |
| Demand response flexibility potential trading in smart grids: A multileader multifollower stackelberg game approach M Yu, J Jiang, X Ye, X Zhang, C Lee, SH Hong IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (5), 2664-2675, 2022 | 14 | 2022 |
| Assessing the traffic scheduling method for time-sensitive networking (TSN) by practical implementation J Jiang, Y Li, X Zhang, M Yu, CD Lee, SH Hong Journal of Industrial Information Integration 33, 100464, 2023 | 12 | 2023 |
| Assessing the feasibility of game-theory-based demand response management by practical implementation M Yu, X Zhang, J Jiang, C Lee, SH Hong, K Wang, A Xu IEEE Access 9, 8220-8232, 2021 | 9 | 2021 |
| Incentivizing strategy for demand response aggregator considering market entry criterion: A game theoretical approach M Yu, SH Hong, X Zhang, J Jiang, X Huang, M Wei, K Wang, W Liang 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1 …, 2019 | 2 | 2019 |
| A Novel YJQR-LSTM Model for Nonparametric Probabilistic Sustainable Agriculture Wind Power Forecasting Based on Intelligent IoT J Wang, J Jiang, X Chen, D Cai, Y Wu, R Lu IEEE Internet of Things Journal, 2024 | 1 | 2024 |
| TSN cfgNCT: Practical Implementation of a TSN Configurator with Negligible Computation Time J Jiang, S Jin, M Yu, WS Song, YC Kim, SH Hong 2024 IEEE 22nd International Conference on Industrial Informatics (INDIN), 2024 | | 2024 |
| Assessing the Traffic Scheduling Method for Time-Sensitive Networking (TSN) from Theory to Practice J Jiang 한양대학교, 2022 | | 2022 |
| Game theoretical-based demand response modeling considering industrial customers M Yu, SH Hong, J Jiang 2018 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems …, 2018 | | 2018 |
Seung Ho HongProfessor, Hanyang University, KoreaBestätigte E-Mail-Adresse bei hanyang.ac.kr