Resource Type

Journal Article 289

Year

2024 23

2023 33

2022 36

2021 29

2020 31

2019 16

2018 18

2017 16

2016 24

2015 16

2014 4

2013 3

2012 3

2011 3

2010 2

2009 2

2008 6

2007 7

2006 3

2005 3

open ︾

Keywords

convolutional neural network 12

neural networks 7

Deep learning 6

deep learning 4

Artificial intelligence 3

Boolean control networks 3

Convolutional neural network 3

machine learning 3

Artificial neural networks 2

Beamforming 2

Boolean networks 2

China 2

Cognitive radio networks 2

Complex networks 2

Consensus 2

Convolutional neural networks (CNNs) 2

Deep convolutional neural network 2

Energy consumption 2

Fault diagnosis 2

open ︾

Search scope:

排序： Display mode:

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    

HTML PDF Collect

A hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process

Frontiers of Chemical Science and Engineering 2024, Volume 18, Issue 4, doi: 10.1007/s11705-024-2403-7

Abstract: In this paper, we propose a novel hybrid spatial-temporal deep learning prediction model to address theseSubsequently, convolutional neural network integrated with the self-attention mechanism are utilizedto extract the temporal patterns.Meanwhile, a multi-graph convolutional network is leveraged to model the spatial interactions.Afterward, the extracted temporal and spatial features are fused as input into a fully connected neural

Keywords： methanol-to-olefins     process variables prediction     spatial-temporal     self-attention mechanism     graphconvolutional network    

HTML PDF Collect

A Spatial–Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays Article

Qing Cai, Sameer Alam, Vu N. Duong

Engineering 2021, Volume 7, Issue 4,   Pages 452-464 doi: 10.1016/j.eng.2020.05.027

Abstract: Specifically, we model air traffic scenarios using spatial-temporal networks with airports as the nodesBased on the constructed spatial–temporal networks, we suggest three metrics—magnitude, severity

Keywords： Air traffic     Transport systems     Delay propagation dynamics     Spatial–temporal networks    

HTML PDF Collect

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

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

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

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 6,   Pages 759-771 doi: 10.1007/s11705-022-2269-5

Abstract: more accurately the product yields and properties than the previously introduced self-organizing-map convolutional

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

HTML PDF Collect

Classifying multiclass relationships between ASes using graph convolutional network

Frontiers of Engineering Management 2022, Volume 9, Issue 4,   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    

HTML PDF Collect

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: Then 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    

HTML PDF Collect

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

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 ofpretrained networks, applying the transfer-learning technique.

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

HTML PDF Collect

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 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

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    

HTML PDF Collect

Automated identification of steel weld defects, a convolutional neural network improved machine learning

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 2,   Pages 294-308 doi: 10.1007/s11709-024-1045-7

Abstract: Classic and convolutional neural network-enhanced algorithms were used to classify, the extracted featuresThe convolutional neural network-enhanced support vector machine (SVM) outperformed six other algorithms

Keywords： steel weld     machine learning     convolutional neural network     weld defect detection     classification task    

HTML PDF Collect

A temporal framework for building up of healthy soils PERSPECTIVE

Frontiers of Agricultural Science and Engineering 2024, Volume 11, Issue 2,   Pages 292-296 doi: 10.15302/J-FASE-2024561

Abstract:

A temporal framework for building up of healthy soils

HTML PDF Collect

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: proposes an image-based deep learning model to estimate urban rainfall intensity with high spatial and temporalMore 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

Title Author Date Type Operation

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 hybrid spatial-temporal deep learning prediction model of industrial methanol-to-olefins process

Journal Article

A Spatial–Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays

Qing Cai, Sameer Alam, Vu N. Duong

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 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

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

Journal Article

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

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

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

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

Automated identification of steel weld defects, a convolutional neural network improved machine learning

Journal Article

A temporal framework for building up of healthy soils

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