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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    

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 convolutionalneural network.The 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    

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    

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 convolutionalneural network.

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

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 convolutionalneural network (SRCNN) technique in the framework of SIMP.

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

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: Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspectiveTo address this issue, this paper explores a decision-tree-structured neural network, that is, the deepconvolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings.The 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    

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.sample database for slope stability analysis reaches more than 99%, and the comparisons with the BP neural

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

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 convolutionalneural network    

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 6, doi: 10.1007/s11783-021-1430-6

Abstract:

• UV-vis absorption analyzer was applied in drainage type online recognition.

Keywords: Drainage online recognition     UV-vis spectra     Derivative spectrum     Convolutional neural network    

A convolutional neural network based approach to sea clutter suppression for small boat detection

Guan-qing Li, Zhi-yong Song, Qiang Fu,liguanqing09@nudt.edu.cn,songzhiyong08@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 10,   Pages 1413-1534 doi: 10.1631/FITEE.1900523

Abstract: In this paper we propose a novel convolutional neural network based dual-activated clutter suppression

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 930-939 doi: 10.1631/FITEE.1500125

Abstract: In this paper we propose a novel method to estimate head pose based on a deep convolutional neural networkThen two convolutional neural networks are set up to train the head pose classifier and then compared

Keywords: Head pose estimation     Deep convolutional neural network     Multiclass classification    

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    

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 2, doi: 10.1007/s11783-023-1622-3

Abstract:

● A novel deep learning framework for short-term water demand forecasting.

Keywords: Short-term water demand forecasting     Long-short term memory neural network     Convolutional Neural Network    

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    

Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic algorithm

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 10,   Pages 1516-1532 doi: 10.1007/s11705-022-2283-7

Abstract: To solve the problem efficiently, a heuristic algorithm combined with a convolutional neural network

Keywords: planning     scheduling     refinery-petrochemical     convolutional neural network     heuristic algorithm    

Title Author Date Type Operation

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

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

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

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

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

Wenxuan CAO; Junjie LI

Journal Article

Online recognition of drainage type based on UV-vis spectra and derivative neural network algorithm

Journal Article

A convolutional neural network based approach to sea clutter suppression for small boat detection

Guan-qing Li, Zhi-yong Song, Qiang Fu,liguanqing09@nudt.edu.cn,songzhiyong08@nudt.edu.cn

Journal Article

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Journal Article

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

Journal Article

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

Journal Article

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic algorithm

Journal Article