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Dynamic gNodeB Sleep Control for Energy-Conserving Radio Access Network Journal article
Shen, Pengfei, Shao, Yulin, Cao, Qi, Lu, Lu. Dynamic gNodeB Sleep Control for Energy-Conserving Radio Access Network[J]. IEEE Transactions on Cognitive Communications and Networking, 2024, 10(4), 1371 - 1385.
Authors:  Shen, Pengfei;  Shao, Yulin;  Cao, Qi;  Lu, Lu
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:7.4/6.9 | Submit date：2024/05/16
Base Station Sleep Control  Ng-ran  Markov Decision Process  Greedy Policy  Index Policy  
Freshness-Aware Resource Allocation for Non-Orthogonal Wireless-Powered IoT Networks Conference paper
Chen, Yunfeng, Liu, Yong, Xiao, Jinhao, Wu, Qunying, Zhang, Han, Hou, Fen. Freshness-Aware Resource Allocation for Non-Orthogonal Wireless-Powered IoT Networks[C]:IEEE, 2024.
Authors:  Chen, Yunfeng;  Liu, Yong;  Xiao, Jinhao;  Wu, Qunying;  Zhang, Han; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0 | Submit date：2024/08/05
Age Of Information  Markov Decision Process  Non-orthogonal Multiple Access  Wireless-powered Iot Network  
Utilizing Deep Reinforcement Learning for High-Voltage Distribution Network Expansion Planning Conference paper
Ou, Zhongxi, Zhang, Liang, Zhao, Xiaoyan, Lan, Wei, Liu, Dundun, Liu, Weifeng. Utilizing Deep Reinforcement Learning for High-Voltage Distribution Network Expansion Planning[C]:Institute of Electrical and Electronics Engineers Inc., 2024, 725-730.
Authors:  Ou, Zhongxi;  Zhang, Liang;  Zhao, Xiaoyan;  Lan, Wei;  Liu, Dundun; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/03
Advantage Actor-critic  Deep Reinforcement Learning  Distribution Network Expansion  Markov Decision Process  
BLER Analysis and Optimal Power Allocation of HARQ-IR for Mission-Critical IoT Communications Journal article
He, Fuchao, Shi, Zheng, Zhou, Binggui, Yang, Guanghua, Li, Xiaofan, Ye, Xinrong, Ma, Shaodan. BLER Analysis and Optimal Power Allocation of HARQ-IR for Mission-Critical IoT Communications[J]. IEEE Internet of Things Journal, 2024.
Authors:  He, Fuchao;  Shi, Zheng;  Zhou, Binggui;  Yang, Guanghua;  Li, Xiaofan; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:8.2/9.0 | Submit date：2024/09/03
Block Error Rate  Decoding  Deep Reinforcement Learning  Fading Channels  Harq-ir  Internet Of Things  Markov Decision Process  Reliability Theory  Resource Management  Short Packet Communications  Signal To Noise Ratio  Throughput  
A Reinforcement Learning Based Coordinated but Differentiated Load Frequency Control Method With Heterogeneous Frequency Regulation Resources Journal article
YuxinMa, Zechun Hu, Yonghua Song. A Reinforcement Learning Based Coordinated but Differentiated Load Frequency Control Method With Heterogeneous Frequency Regulation Resources[J]. IEEE Transactions on Power Systems, 2023, 39(1), 2239-2250.
Authors:  YuxinMa;  Zechun Hu;  Yonghua Song
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:6.5/7.4 | Submit date：2023/08/03
Delays  Energy Storage Systems  Frequency Control  Generators  Load Frequency Control  Mathematical Models  Partially Observable Markov Decision Process  Power System Stability  Proximal Policy Optimization  Regulation  Renewable Energy Resources  Renewable Energy Sources  
A Deep Reinforcement Learning Recommender System With Multiple Policies for Recommendations Journal article
Mingsheng Fu, Liwei Huang, Ananya Rao, Athirai A. Irissappane, Jie Zhang, Hong Qu. A Deep Reinforcement Learning Recommender System With Multiple Policies for Recommendations[J]. IEEE Transactions on Industrial Informatics, 2022, 19(2), 2049-2061.
Authors:  Mingsheng Fu;  Liwei Huang;  Ananya Rao;  Athirai A. Irissappane;  Jie Zhang; et al.
Favorite | TC[WOS]:6 TC[Scopus]:7  IF:11.7/11.4 | Submit date：2023/02/22
Deep Reinforcement Learning (Drl)  Multitask Markov Decision Process (Mdp)  Recommender System  
Reinforcement Learning Enabled Dynamic Resource Allocation in the Internet of Vehicles Journal article
Liang, Hongbin, Zhang, Xiaohui, Hong, Xintao, Zhang, Zongyuan, Li, Mushu, Hu, Guangdi, Hou, Fen. Reinforcement Learning Enabled Dynamic Resource Allocation in the Internet of Vehicles[J]. IEEE Transactions on Industrial Informatics, 2021, 17(7), 4957-4967.
Authors:  Liang, Hongbin;  Zhang, Xiaohui;  Hong, Xintao;  Zhang, Zongyuan;  Li, Mushu; et al.
Favorite | TC[WOS]:29 TC[Scopus]:37  IF:11.7/11.4 | Submit date：2021/12/08
Hierarchical Architecture  Internet Of Vehicles (Iov)  Reinforcement Learning  Resource Allocation  Semi-markov Decision Process (Smdp)  
Risk-sensitive semi-Markov decision processes with general utilities and multiple criteria Journal article
YONGHUI HUANG, ZHAOTONG LIAN, XIANPING GUO. Risk-sensitive semi-Markov decision processes with general utilities and multiple criteria[J]. Advances in Applied Probability, 2018, 50(3), 783-804.
Authors:  YONGHUI HUANG;  ZHAOTONG LIAN;  XIANPING GUO
Favorite | TC[WOS]:7 TC[Scopus]:7  IF:0.9/1.1 | Submit date：2019/08/01
Expected Utility  Finite-horizon Cost  Linear Program  Occupation Measure  Semi-markov Decision Process  
Learning-based web service composition in uncertain environments Journal article
Yu L., Wang Z., Meng L., Qiu X., Zhou J.. Learning-based web service composition in uncertain environments[J]. Journal of Web Engineering, 2014, 13(5-6), 450-468.
Authors:  Yu L.;  Wang Z.;  Meng L.;  Qiu X.;  Zhou J.
Favorite |  | Submit date：2018/12/22
Optimal policy  Partially observable markov decision process  Reinforcement learning algorithm  Success rate of service composition  Web service composition  
Autonomous behaviors of graphical avatars based on machine learning Journal article
YUESHENG HE, YUAN YAN TANG. Autonomous behaviors of graphical avatars based on machine learning[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2012, 26(2).
Authors:  YUESHENG HE;  YUAN YAN TANG
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:0.9/1.0 | Submit date：2019/02/11
3d Avatars  3d Graphical Environment  3d Graphical Models  Markov Decision Process  Reinforcement Learning  Support Vector Machine  Virtual Human