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Deep learning model for solar and wind energy forecasting considering Northwest China as an example Journal article
Li, Pengyu, Yang, Huiyu, Wu, Han, Wang, Yujia, Su, Hao, Zheng, Tianlong, Zhu, Fang, Zhang, Guangtao, Han, Yu. Deep learning model for solar and wind energy forecasting considering Northwest China as an example[J]. Results in Engineering, 2024, 24, 102939.
Authors:  Li, Pengyu;  Yang, Huiyu;  Wu, Han;  Wang, Yujia;  Su, Hao; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:6.0/5.6 | Submit date：2024/10/10
Attention-based Spatial-temporal Graph Neural Network  Deep Learning  Long Short-term Memory  Solar Energy  Wind Energy  
Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks Conference paper
Duan, Wenying, Fang, Tianxiang, Rao, Hong, He, Xiaoxi. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks[C], New York, NY, USA:Association for Computing Machinery, 2024, 701-712.
Authors:  Duan, Wenying;  Fang, Tianxiang;  Rao, Hong;  He, Xiaoxi
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Lottery Ticket Hypothesis  Spatial-temporal Data Mining  Spatial-temporal Graph Neural Network  
FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction Conference paper
Yang, Linghua, Chen, Wantong, He, Xiaoxi, Wei, Shuyue, Xu, Yi, Zhou, Zimu, Tong, Yongxin. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction[C], New York, NY, USA:Association for Computing Machinery, 2024, 6105–6116.
Authors:  Yang, Linghua;  Chen, Wantong;  He, Xiaoxi;  Wei, Shuyue;  Xu, Yi; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Federated Learning  Traffic Prediction  Spatial-temporal Graph Neural Network  
Localised Adaptive Spatial-Temporal Graph Neural Network Conference paper
Duan, Wenying, He, Xiaoxi, Zhou, Zimu, Thiele, Lothar, Rao, Hong. Localised Adaptive Spatial-Temporal Graph Neural Network[C]:ASSOC COMPUTING MACHINERY1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES, 2023, 448-458.
Authors:  Duan, Wenying;  He, Xiaoxi;  Zhou, Zimu;  Thiele, Lothar;  Rao, Hong
Favorite | TC[WOS]:1 TC[Scopus]:5 | Submit date：2024/01/10
Graph Sparsification  Spatial-temporal Data  Spatial-temporal Graph Neural Network  
Broad Graph Convolutional Neural Network and Its Application in Hyperspectral Image Classification Journal article
Wang, Haoyu, Cheng, Yuhu, Chen, C. L.Philip, Wang, Xuesong. Broad Graph Convolutional Neural Network and Its Application in Hyperspectral Image Classification[J]. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023, 7(2), 610-616.
Authors:  Wang, Haoyu;  Cheng, Yuhu;  Chen, C. L.Philip;  Wang, Xuesong
Favorite | TC[WOS]:18 TC[Scopus]:15  IF:5.3/5.7 | Submit date：2023/05/02
Broad Learning  Graph Convolution  Hyperspectral Image Classification  Spectral-spatial Feature  
Reinforced Imitative Graph Learning for Mobile User Profiling Journal article
Dongjie Wang, Pengyang Wang, Kunpeng Liu, Xiong, Hui, Charles Hughes, Yanjie Fu. Reinforced Imitative Graph Learning for Mobile User Profiling[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(12), 12944-12957.
Authors:  Dongjie Wang;  Pengyang Wang;  Kunpeng Liu;  Xiong, Hui;  Charles Hughes; et al.
Favorite | TC[WOS]:7 TC[Scopus]:5  IF:8.9/8.8 | Submit date：2023/07/18
Behavioral Sciences  Education  Incremental Learning  Knowledge Graphs  Mobile User Profiling  Reinforcement Learning  Reinforcement Learning  Semantics  Spatial Knowledge Graph  Tail  Task Analysis  
A graph-attention based spatial-temporal learning framework for tourism demand forecasting Journal article
Zhou, Binggui, Dong, Yunxuan, Yang, Guanghua, Hou, Fen, Hu, Zheng, Xu, Suxiu, Ma, Shaodan. A graph-attention based spatial-temporal learning framework for tourism demand forecasting[J]. Knowledge-Based Systems, 2023, 263, 110275.
Authors:  Zhou, Binggui;  Dong, Yunxuan;  Yang, Guanghua;  Hou, Fen;  Hu, Zheng; et al.
Favorite | TC[WOS]:6 TC[Scopus]:8  IF:7.2/7.4 | Submit date：2023/04/03
Tourism Demand Forecasting  Dynamic Spatial Connections  Spatial-temporal Learning  Graph Neural Network  Attention Mechanism  
Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing Journal article
Wang, Dongjie, Liu, Kunpeng, Mohaisen, David, Wang, Pengyang, Lu, Chang Tien, Fu, Yanjie. Towards Semantically-Rich Spatial Network Representation Learning via Automated Feature Topic Pairing[J]. Frontiers in Big Data, 2021, 4, 762899.
Authors:  Wang, Dongjie;  Liu, Kunpeng;  Mohaisen, David;  Wang, Pengyang;  Lu, Chang Tien; et al.
Favorite | TC[WOS]:3 TC[Scopus]:4 | Submit date：2021/12/08
Feature-topic Pairing  Semantic Space  Spatial Graph  Spatial Representation Learning  Spatial Space  
ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting Conference paper
Tian,Kelang, Guo,Jingjie, Ye,Kejiang, Xu,Cheng Zhong. ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting[C], 2020, 714-721.
Authors:  Tian,Kelang;  Guo,Jingjie;  Ye,Kejiang;  Xu,Cheng Zhong
Favorite | TC[WOS]:8 TC[Scopus]:10 | Submit date：2021/03/09
Graph Convolutional Networks  Spatial-temporal Model  Traffic Forecasting  
Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax Journal article
Han Z., Liu Z., Vong C.-M., Liu Y.-S., Bu S., Han J., Chen C.L.P.. Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network with Coupled Softmax[J]. IEEE Transactions on Image Processing, 2018, 27(6), 3049-3063.
Authors:  Han Z.;  Liu Z.;  Vong C.-M.;  Liu Y.-S.;  Bu S.; et al.
Favorite | TC[WOS]:37 TC[Scopus]:43 | Submit date：2019/02/11
Coupled Softmax  Deep Spatial  Directed Circular Graph  Spatially-enhanced 3d Features