Resource Type

Journal Article 334

Conference Videos 4

Conference Information 2

Year

2023 12

2022 41

2021 34

2020 43

2019 32

2018 19

2017 14

2016 18

2015 18

2014 6

2013 9

2012 3

2011 2

2010 5

2009 4

2008 9

2007 14

2006 5

2005 8

2004 8

open ︾

Keywords

neural network 30

artificial neural network 20

Artificial intelligence 8

Deep learning 7

Neural network 7

neural networks 7

artificial neural network (ANN) 6

convolutional neural network 6

genetic algorithm 6

BP neural network 4

optimization 4

ANN 3

finite element method 3

ANOVA 2

Artificial neural network 2

Artificial neural networks 2

BP algorithm 2

Boolean control networks 2

Boolean networks 2

open ︾

Search scope:

排序： Display mode:

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

Frontiers of Structural and Civil Engineering   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 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    

HTML PDF Collect
Share

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    

HTML PDF Collect
Share

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 ofpretrained networks, applying the transfer-learning technique.

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

HTML PDF Collect
Share

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    

HTML PDF Collect
Share

Slope stability analysis based on big data and convolutional neural network

Frontiers of Structural and Civil Engineering   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    

HTML PDF Collect
Share

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

Frontiers of Structural and Civil Engineering   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    

HTML PDF Collect
Share

Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Frontiers of Chemical Science and Engineering doi: 10.1007/s11705-022-2269-5

Abstract: The model is comprised of self-organizing-map and the neural network parts.self-organizing-map part maps the input data into multiple two-dimensional planes and sends them to the neuralIn the neural network part, residual blocks enhance the convergence and accuracy, ensuring that the structuremore accurately the product yields and properties than the previously introduced self-organizing-map convolutionalneural network model, thus leading to more accurate optimization of the hydrocracker operation.

Keywords： hydrocracking     convolutional neural networks     self-organizing map     deep learning     data-driven optimization    

HTML PDF Collect
Share

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

Frontiers of Mechanical Engineering   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    

HTML PDF Collect
Share

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    

HTML PDF Collect
Share

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    

HTML PDF Collect
Share

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    

HTML PDF Collect
Share

Novel interpretable mechanism of neural networks based on network decoupling method

Frontiers of Engineering Management 2021, Volume 8, Issue 4,   Pages 572-581 doi: 10.1007/s42524-021-0169-x

Abstract: The lack of interpretability of the neural network algorithm has become the bottleneck of its wide applicationdecoupled dimension reduction method of high-dimensional system and reveal the calculation mechanism of the neuralthat a simple linear mapping relationship exists between network structure and network behavior in the neuralnew interpretation mechanism provides not only the potential mathematical calculation principle of neuralor animal activities, which can further expand and enrich the interpretable mechanism of artificial neural

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

HTML PDF Collect
Share

Recent advances in efficient computation of deep convolutional neural networks Review

Jian CHENG, Pei-song WANG, Gang LI, Qing-hao HU, Han-qing LU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 1,   Pages 64-77 doi: 10.1631/FITEE.1700789

Abstract: Deep neural networks have evolved remarkably over the past few years and they are currently the fundamentalAt the same time, the computational complexity and resource consumption of these networks continue toThis poses a significant challenge to the deployment of such networks, especially in real-time applicationsAs for hardware implementation of deep neural networks, a batch of accelerators based on a field-programmablethe following topics: network pruning, low-rank approximation, network quantization, teacher–student networks

Keywords： Deep neural networks     Acceleration     Compression     Hardware accelerator    

HTML PDF Collect
Share

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

Frontiers of Structural and Civil Engineering   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 convolutionalThe TCN model is found outperforming the recurrent neural network (RNN) and long short-term memory (LSTM

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

HTML PDF Collect
Share

Estimating Rainfall Intensity Using an Image-Based Deep Learning Model Article

Hang Yin, Feifei Zheng, Huan-Feng Duan, Dragan Savic, Zoran Kapelan

Engineering 2023, Volume 21, Issue 2,   Pages 162-174 doi: 10.1016/j.eng.2021.11.021

Abstract: More specifically, a convolutional neural network (CNN) model called the image-based rainfall CNN (irCNN

Keywords： Urban flooding     Rainfall images     Deep learning model     Convolutional neural networks (CNNs)     Rainfall    

HTML PDF Collect
Share

Title Author Date Type Operation

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

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

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

Journal Article

Slope stability analysis based on big data and convolutional neural network

Journal Article

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

Journal Article

Multiple input self-organizing-map ResNet model for optimization of petroleum refinery conversion units

Journal Article

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

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

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

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article

Recent advances in efficient computation of deep convolutional neural networks

Jian CHENG, Pei-song WANG, Gang LI, Qing-hao HU, Han-qing LU

Journal Article

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

Journal Article

Estimating Rainfall Intensity Using an Image-Based Deep Learning Model

Hang Yin, Feifei Zheng, Huan-Feng Duan, Dragan Savic, Zoran Kapelan

Journal Article