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A knowledge matching approach based on multi-classification radial basis function neural network for Research Articles

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900057

Abstract: In addition, we propose a multi-classification radial basis function neural network that can match the

Keywords： Product design     Knowledge push system     Augmented training set     Multi-classification neural network     Knowledge    

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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 potential

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

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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: To overcome this challenge, this paper presents a method for automating concrete damage classificationusing a deep convolutional neural network.The convolutional neural network was designed after an experimental investigation of a wide number ofmodel, with the highest validation accuracy of approximately 94%, was selected as the most suitable networkfor concrete damage classification.

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

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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 pistonunder different pump health conditions are fused into RGB images and then recognized by a convolutional neuralnetwork.Results 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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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 comparedBefore training the network, two reasonable strategies including shift and zoom are executed to prepareFinally, feature extraction filters are optimized together with the weight of the classification componentthrough training, to minimize the classification error.

Keywords： Head pose estimation     Deep convolutional neural network     Multiclass classification    

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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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Assessing artificial neural network performance for predicting interlayer conditions and layer modulusof multi-layered flexible pavement

Lingyun YOU, Kezhen YAN, Nengyuan LIU

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 2,   Pages 487-500 doi: 10.1007/s11709-020-0609-4

Abstract: The objective of this study is to evaluate the performance of the artificial neural network (ANN) approachfor predicting interlayer conditions and layer modulus of a multi-layered flexible pavement structure

Keywords： asphalt pavement     interlayer conditions     finite element method     artificial neural network     back-calculation    

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Research on the credit classification of practicing qualification personnel in construction market basedon self-organizing neural network

Fang Zhiqing,Wang Xueqing,Li Baolong

Strategic Study of CAE 2011, Volume 13, Issue 9,   Pages 105-108

Abstract: qualification personnel in construction market, evaluation method based on the self-organizing nerural networkis brought out to analyze the credit classification of the practicing qualification personnel.And the impact factors on the credit classification of the practicing qualification personnel, such asThen a self-organizing competitive neural network is built.

Keywords： practicing qualification personnel     credit     cluster analysis     self-organizing neural network    

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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 toTo further improve the classification performance, the classifier of the classification module is redesignedWith the help of contrastive learning, the classification module can better initialize the category-wiseExperiments on the mobile screen defect dataset show that our two-stage network achieves the following

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

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Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1285-1298 doi: 10.1007/s11709-020-0691-7

Abstract: The neural networks can be used to construct fully decoupled approaches in nonlinear multiscale methodsThis article intends to model the multiscale constitution using feedforward neural network (FNN) andrecurrent neural network (RNN), and appropriate set of loading paths are selected to effectively predict

Keywords： multiscale method     constitutive model     feedforward neural network     recurrent neural network    

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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     Wavelet multi-resolution analysis     Data-driven models    

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Shot classification and replay detection for sports video summarization Research Article

Ali JAVED, Amen ALI KHAN,ali.javed@uettaxila.edu.pk

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 790-800 doi: 10.1631/FITEE.2000414

Abstract: For this purpose, we propose local octa-pattern features to represent video frames and train the for classification

Keywords： Extreme learning machine     Lightweight convolutional neural network     Local octa-patterns     Shot classification    

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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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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 applicationnetwork.Result shows that a simple linear mapping relationship exists between network structure and network behaviorin the neural network with high-dimensional and nonlinear characteristics.which can further expand and enrich the interpretable mechanism of artificial neural network in the future

Keywords： neural networks     interpretability     dynamical behavior     network decouple    

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Urban landscape classification using Chinese advanced high-resolution satellite imagery and an object-orientedmulti-variable model

Li-gang MA,Jin-song DENG,Huai YANG,Yang HONG,Ke WANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 238-248 doi: 10.1631/FITEE.1400083

Abstract: Its capability for comprehensive landscape classification, especially in urban areas, has been underand heterogeneity across urban environments, we attempt to test its performance of urban landscape classificationselected using forward stepwise linear discriminant analysis and applied in the following object-oriented classificationResults indicated an overall classification accuracy of 92.63% and a kappa statistic of 0.9124.presented method and the Chinese ZY-1 02C satellite imagery are robust and effective for urban landscape classification

Keywords： ZY-1 02C satellite     Classification     Urban     Multi-variable model    

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Title Author Date Type Operation

A knowledge matching approach based on multi-classification radial basis function neural network for

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Journal Article

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

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

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Journal Article

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

Journal Article

Assessing artificial neural network performance for predicting interlayer conditions and layer modulusof multi-layered flexible pavement

Lingyun YOU, Kezhen YAN, Nengyuan LIU

Journal Article

Research on the credit classification of practicing qualification personnel in construction market basedon self-organizing neural network

Fang Zhiqing,Wang Xueqing,Li Baolong

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

Multiscale computation on feedforward neural network and recurrent neural network

Bin LI, Xiaoying ZHUANG

Journal Article

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

Journal Article

Shot classification and replay detection for sports video summarization

Ali JAVED, Amen ALI KHAN,ali.javed@uettaxila.edu.pk

Journal Article

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

Journal Article

Novel interpretable mechanism of neural networks based on network decoupling method

Journal Article

Urban landscape classification using Chinese advanced high-resolution satellite imagery and an object-orientedmulti-variable model

Li-gang MA,Jin-song DENG,Huai YANG,Yang HONG,Ke WANG

Journal Article