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Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutionalnetworks 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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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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Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 3,   Pages 480-480 doi: 10.1631/FITEE.22e0073

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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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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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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: previous fault diagnosis methods only used vibration or pressure signal, and literatures related to multi-sensorThis paper presents an end-to-end multi-sensor data fusion method for the fault diagnosis of axial pistonpressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutionalResults show that the proposed multi-sensor data fusion method greatly improves the fault diagnosis of

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

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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: The paper proposes a multi-level strategy, designed and implemented on the basis of periodic structuralSuch strategy leverages the high capacity of convolutional neural networks to identify and classify potentialprofiles and the revealed structural phenomena have been used as input and output to train and test such networks

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

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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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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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A graph-based two-stage classification network for mobile screen defect inspection Research Article

Chaofan ZHOU, Meiqin LIU, Senlin ZHANG, Ping WEI, Badong CHEN

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 2,   Pages 203-216 doi: 10.1631/FITEE.2200524

Abstract: low contrast, tiny-sized, or incomplete defects, and (3) the modeling of category dependencies for multi-labelTo solve these problems, a graph reasoning module, stacked on a classification module, is proposed tothe help of contrastive learning, the classification module can better initialize the category-wise graph

Keywords： Graph-based methods     Multi-label classification     Mobile screen defects     Neural networks    

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A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0736-9

Abstract: Given the advantage of obtaining accurate diagnosis results, multi-sensor fusion has long been studiedSecond, the localization for multi-source faults is seldom investigated, although locating the anomalyweaknesses by proposing a global method to recognize fault types and localize fault sources with the help of multi-sensor

Keywords： fault recognition     fault localization     multi-sensor relations     network analysis     graph neural network    

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Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 429-448 doi: 10.1631/FITEE.1500118

Abstract: This paper reviews some main results and progress in distributed multi-agent coordination from a graphDistributed multi-agent coordination has been a very active subject studied extensively by the systemsThe aim of this paper is to provide both a comprehensive survey of existing literature in distributed multi-agentcoordination and a new perspective in terms of graph Laplacian to categorize the fundamental mechanismsFor different types of graph Laplacians, we summarize their inherent coordination features and specific

Keywords： Multi-agent systems     Distributed coordination     Graph Laplacian    

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Multi-focus image fusion based on fully convolutional networks Research Articles

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900336

Abstract: We propose a method, in which a fully convolutional network for focus detection (FD-FCN) is constructed

Keywords： 多焦距图像融合；全卷积网络；跳层；性能评估    

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A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3 Regular Papers

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 3,   Pages 405-413 doi: 10.1631/FITEE.1700413

Abstract: In this study, we present a novel method based on convolutional neural networks (CNNs) for the synthesis

Keywords： Convolutional neural networks (CNNs)     Electrocardiogram (ECG) synthesis     E-health    

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A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of thin-walled structural components

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0688-0

Abstract: classification schemes have been considered in this study: those that perform feature extraction by using the convolutionalneural networks and those based on an explicit feature extraction procedure.

Keywords： precision milling     dimensional accuracy     cutting force     convolutional neural networks     coherent noise    

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Title Author Date Type Operation

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

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Journal Article

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Journal Article

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

Wenxuan CAO; Junjie 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

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

Journal Article

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

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

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

A graph-based two-stage classification network for mobile screen defect inspection

Chaofan ZHOU, Meiqin LIU, Senlin ZHANG, Ping WEI, Badong CHEN

Journal Article

A multi-sensor relation model for recognizing and localizing faults of machines based on network analysis

Journal Article

Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Journal Article

Multi-focus image fusion based on fully convolutional networks

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Journal Article

A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Journal Article

A hybrid deep learning model for robust prediction of the dimensional accuracy in precision milling of thin-walled structural components

Journal Article