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Classifying multiclass relationships between ASes using graph convolutional network

Frontiers of Engineering Management   Pages 653-667 doi: 10.1007/s42524-022-0217-1

Abstract: We then introduce new features and propose a graph convolutional network (GCN) framework, AS-GCN, to

Keywords： autonomous system     multiclass relationship     graph convolutional network     classification algorithm     Internet    

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Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 11,   Pages 1378-1396 doi: 10.1007/s11709-022-0855-8

Abstract: The graph convolutional neural network (GCN) was used to segment the stitched image.The GCN’s m-IOU is 24.02% higher than Fully convolutional networks (FCN), proving that GCN has

Keywords： underwater cracks     remote operated vehicle     image stitching     image segmentation     graph convolutional    

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Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional Research Article

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1848-1861 doi: 10.1631/FITEE.2200035

Abstract: system's spatial information such as the electrical distance to increase the accuracy in the process of graphuses power system topology and spatial information to optimize the edge weight assignment of the line graphThen we propose a multi-graph convolutional network (MGCN) based on a graph classification task, which

Keywords： Power systems     Vulnerability     Cascading failures     Multi-graph convolutional networks     Weighted line graph    

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A local density optimization method based on a graph convolutional network

Hao Wang, Li-yan Dong, Tie-hu Fan, Ming-hui Sun,wanghao18@mails.jlu.edu.cn,dongly@jlu.edu.cn,fth@jlu.edu.cn,smh@jlu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 12,   Pages 1671-1814 doi: 10.1631/FITEE.1900663

Abstract: Success has been obtained using a semi-supervised graph analysis method based on a (GCN).However, GCN ignores some local information at each node in the graph, so that data preprocessing isFinally, we compare the performances of several mainstream graph analysis algorithms with that of the
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Video summarization with a graph convolutional attention network Research Articles

Ping Li, Chao Tang, Xianghua Xu,patriclouis.lee@gmail.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 902-913 doi: 10.1631/FITEE.2000429

Abstract: To address the above problem, we propose a graph convolutional attention network (GCAN) for .consists of two parts, embedding learning and , where embedding learning includes the temporal branch and graphIt learns graph embedding via a multi-layer to reveal the intrinsic structure of frame samples.The part combines the output streams from the temporal branch and graph branch to create the context-aware

Keywords： 时序学习；自注意力机制；图卷积网络；上下文融合；视频摘要    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 305-317 doi: 10.1007/s11709-021-0725-9

Abstract: challenge, this paper presents a method for automating concrete damage classification using a deep convolutionalThe convolutional neural network was designed after an experimental investigation of a wide number of

Keywords： concrete structure     infrastructures     visual inspection     convolutional neural network     artificial intelligence    

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Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 214-223 doi: 10.1007/s11709-021-0800-2

Abstract: Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential

Keywords： concrete structure     GPR     damage classification     convolutional neural network     transfer learning    

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Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0692-4

Abstract: pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional

Keywords： axial piston pump     fault diagnosis     convolutional neural network     multi-sensor data fusion    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutionalThe proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network    

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Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 882-895 doi: 10.1007/s11709-022-0859-4

Abstract: In this case, the convolutional neural network (CNN) provides a better alternative.

Keywords： slope stability     limit equilibrium method     convolutional neural network     database for slopes     big data    

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Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 1,   Pages 80-96 doi: 10.1007/s11465-020-0614-2

Abstract: efficient, high-resolution topology optimization method is developed based on the super-resolution convolutional

Keywords： topology optimization     convolutional neural network     high resolution     density-based    

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Large-scale graph processing systems: a survey Review

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 384-404 doi: 10.1631/FITEE.1900127

Abstract: Graph is a significant data structure that describes the relationship between entries.Many application domains in the real world are heavily dependent on graph data.However, graph applications are vastly different from traditional applications.of specific graph processing platforms.In this survey, we systematically categorize the graph workloads and applications, and provide a detailed

Keywords： Graph workloads     Graph applications     Graph processing systems    

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Forecasting traffic flows in irregular regions with multi-graph convolutional network and gated recurrent Research Articles

Dewen Seng, Fanshun Lv, Ziyi Liang, Xiaoying Shi, Qiming Fang,sengdw@hdu.edu.cn,172050041@hdu.edu.cn,liangziyi2020@163.com,shixiaoying@hdu.edu.cn,fangqiming@hdu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9,   Pages 1179-1193 doi: 10.1631/FITEE.2000243

Abstract: With the help of deep neural networks, the convolutional neural network or residual neural network, whichIn each graph, nodes represent the and edges represent the relationship types between regions.

Keywords： 交通流量预测；多图卷积网络；门控循环单元；不规则区域    

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Realtime prediction of hard rock TBM advance rate using temporal convolutional network (TCN) with tunnel

Zaobao LIU; Yongchen WANG; Long LI; Xingli FANG; Junze WANG

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 4,   Pages 401-413 doi: 10.1007/s11709-022-0823-3

Abstract: This paper proposes a real-time predictive model of TBM advance rate using the temporal convolutional

Keywords： hard rock tunnel     tunnel bore machine advance rate prediction     temporal convolutional networks     soft    

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Title Author Date Type Operation

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Journal Article

Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Journal Article

A local density optimization method based on a graph convolutional network

Hao Wang, Li-yan Dong, Tie-hu Fan, Ming-hui Sun,wanghao18@mails.jlu.edu.cn,dongly@jlu.edu.cn,fth@jlu.edu.cn,smh@jlu.edu.cn

Journal Article

Video summarization with a graph convolutional attention network

Ping Li, Chao Tang, Xianghua Xu,patriclouis.lee@gmail.com

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Journal Article

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Journal Article

Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article

Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Journal Article

Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

Journal Article

Large-scale graph processing systems: a survey

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Journal Article

Forecasting traffic flows in irregular regions with multi-graph convolutional network and gated recurrent

Dewen Seng, Fanshun Lv, Ziyi Liang, Xiaoying Shi, Qiming Fang,sengdw@hdu.edu.cn,172050041@hdu.edu.cn,liangziyi2020@163.com,shixiaoying@hdu.edu.cn,fangqiming@hdu.edu.cn

Journal Article

Realtime prediction of hard rock TBM advance rate using temporal convolutional network (TCN) with tunnel

Zaobao LIU; Yongchen WANG; Long LI; Xingli FANG; Junze WANG

Journal Article