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Efficient quaternion CUR method for low-rank approximation to quaternion matrix Journal article
Pengling Wu, Kit Ian Kou, Hongmin Cai, Zhaoyuan Yu. Efficient quaternion CUR method for low-rank approximation to quaternion matrix[J]. Numerical Algorithms, 2024.
Authors:  Pengling Wu;  Kit Ian Kou;  Hongmin Cai;  Zhaoyuan Yu
Adobe PDF | Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.7/1.9 | Submit date：2024/08/20
65f55  Color Image Processing  Low-rank Approximation  Quaternion Cur Decomposition  Quaternion Matrix  
Hypercomplex Signal Processing in Digital Twin of the Ocean: Theory and application Journal article
Zhaoyuan Yu, Dongshuang Li, Pei Du, Wen Luo, Kit Ian Kou. Hypercomplex Signal Processing in Digital Twin of the Ocean: Theory and application[J]. IEEE Signal Processing Magazine, 2024, 41(3).
Authors:  Zhaoyuan Yu;  Dongshuang Li;  Pei Du;  Wen Luo;  Kit Ian Kou
Adobe PDF | Favorite |   IF:9.4/18.0 | Submit date：2024/08/21
Hypercomplex Signal Processing in Digital Twin of the Ocean: Theory and application [Hypercomplex Signal and Image Processing] Journal article
Yu, Zhaoyuan, Li, Dongshuang, Du, Pei, Luo, Wen, Kou, Kit Ian, Bhatti, Uzair Aslam, Benger, Werner, Lv, Guonian, Yuan, Linwang. Hypercomplex Signal Processing in Digital Twin of the Ocean: Theory and application [Hypercomplex Signal and Image Processing][J]. IEEE Signal Processing Magazine, 2024, 41(3), 33-48.
Authors:  Yu, Zhaoyuan;  Li, Dongshuang;  Du, Pei;  Luo, Wen;  Kou, Kit Ian; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:9.4/18.0 | Submit date：2024/09/03
Analytical Models  Computational Modeling  Data Visualization  Geoscience  Signal Processing  Predictive Models  Hypercomplex  Digital Twins  Oceanography  Artificial Intelligence  High Performance Computing  
Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning Journal article
Wang, Zhaoyuan, Pan, Zheyi, Chen, Shun, Ji, Shenggong, Yi, Xiuwen, Zhang, Junbo, Wang, Jingyuan, Gong, Zhiguo, Li, Tianrui, Zheng, Yu. Shortening passengers' travel time: A dynamic metro train scheduling approach using deep reinforcement learning[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 35(5), 5282-5295.
Authors:  Wang, Zhaoyuan;  Pan, Zheyi;  Chen, Shun;  Ji, Shenggong;  Yi, Xiuwen; et al.
Favorite | TC[WOS]:1 TC[Scopus]:3  IF:8.9/8.8 | Submit date：2022/05/17
Metro Systems  Spatio-temporal Data  Neural Network  Deep Reinforcement Learning  Urban Computing