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Multi-class dynamic network traffic flow propagation model with physical queues

Yanfeng LI, Jun LI

Frontiers of Engineering Management 2017, Volume 4, Issue 4,   Pages 399-407 doi: 10.15302/J-FEM-2017041

Abstract: This paper proposes an improved multi-class dynamic network traffic flow propagation model with a considerationThe vehicles of the same class are assumed to satisfy the first-in-first-out (FIFO) principle on theanalysis can more realistically capture the traffic flow propagation, such as interactions between multi-class

Keywords： first-in-first-out (FIFO)     multi-class traffic     physical queues     traffic flow modeling    

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Identification of thermal error in a feed system based on multi-class LS-SVM

Chao JIN, Bo WU, Youmin HU, Yao CHENG

Frontiers of Mechanical Engineering 2012, Volume 7, Issue 1,   Pages 47-54 doi: 10.1007/s11465-012-0307-6

Abstract: Using multi-class least squares support vector machines (LS-SVM), the thermal positioning error of the

Keywords： least squares support vector machine (LS-SVM)     feed system     thermal error     precision machining    

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Side-channel attacks and learning-vector quantization Article

Ehsan SAEEDI, Yinan KONG, Md. Selim HOSSAIN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 511-518 doi: 10.1631/FITEE.1500460

Abstract: The main characteristics of LVQ as a multi-class classifier are that it has the ability to learn complexExperimental results show the performance of multi-class classification based on LVQ as a powerful and

Keywords： Side-channel attacks     Elliptic curve cryptography     Multi-class classification     Learning vector quantization    

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Max-margin basedBayesian classifier Article

Tao-cheng HU,Jin-hui YU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10,   Pages 973-981 doi: 10.1631/FITEE.1601078

Abstract: There is a tradeoff between generalization capability and computational overhead in multi-class learningWe propose a generative probabilistic multi-class classifier, considering both the generalization capability

Keywords： Multi-class learning     Max-margin learning     Online algorithm    

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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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Supervised topic models with weighted words: multi-label document classification None

Yue-peng ZOU, Ji-hong OUYANG, Xi-ming LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 513-523 doi: 10.1631/FITEE.1601668

Abstract: Supervised topic modeling algorithms have been successfully applied to multi-label document classificationa word has occurred in the training data), which is significant for classification.To address this, we propose a method, namely the class frequency weight (CF-weight), to weight wordsby considering the class frequency knowledge.A number of experiments have been conducted on real-world multi-label datasets.

Keywords： Supervised topic model     Multi-label classification     Class frequency     Labeled latent Dirichlet allocation    

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A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumerelectrical appliances classification

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

Frontiers in Energy 2019, Volume 13, Issue 2,   Pages 386-398 doi: 10.1007/s11708-017-0497-z

Abstract: The classification algorithm performs cropping and image pyramid reduction of the - trajectory plotsystematic approach of load disaggregation through - trajectory-based load signature images by utilizing a multi-stageclassification algorithm methodology.the number of closest data points to the nearest neighbor, in the -NN algorithm to be effective in classificationThe results of the multi-stage classification algorithm implementation have been discussed and the idea

Keywords： load disaggregation     voltage-current (V-I) trajectory     multi-stage classification algorithm    

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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 292-298 doi: 10.1007/s11465-006-0022-2

Abstract: To deal with pattern classification of complicated mechanical faults, an approach to multi-faults classificationKPCA is good at detection of machine abnormality while GDA performs well in multi-faults classificationWhen the proposed method is applied to air compressor condition classification and gear fault classification, an excellent performance in complicated multi-faults classification is presented.

Keywords： generalized discriminant     non-separable     abnormality     classification     multi-faults classification    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning andunary classification

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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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 structural

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

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A survey of instantaneous poles for a class of two-degree-of-freedom spherical mechanisms

Soheil ZARKANDI

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 4,   Pages 344-353 doi: 10.1007/s11465-014-0320-z

Abstract:

This paper is a detailed exploration of instantaneous poles for a class of two-degree-of-freedom (

Keywords： spherical mechanisms     instantaneous poles     Aronhold-Kennedy theorem     great circles     pencil of meridian    

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Unified cycle model of a class of internal combustion engines and their optimum performance characteristics

Shiyan ZHENG

Frontiers in Energy 2011, Volume 5, Issue 4,   Pages 367-375 doi: 10.1007/s11708-011-0170-x

Abstract: The unified cycle model of a class of internal combustion engines is presented, in which the influenceof the multi-irreversibilities mainly resulting from the adiabatic processes, finite-time processes

Keywords： internal combustion engine     irreversibility     power output     efficiency     optimization    

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Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 4,   Pages 448-455 doi: 10.1007/s11709-014-0262-x

Abstract: Rock mass classification system is very suitable for various engineering design and stability analysisclassification method is confirmed by Japan Highway Public Corporation that this method can figure outThese equations as a new method were able to optimize the support system for and classification systemsFrom classification and its application in these case studies, it is pointed out that the methodfor the design of support systems in underground working is more reliable than the and classification

Keywords： JH classification     Q and RMR classification     new method    

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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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Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

Frontiers of Medicine 2018, Volume 12, Issue 2,   Pages 229-235 doi: 10.1007/s11684-017-0581-0

Abstract: Taking gastric cancer as an example, its molecular classification is built on genome abnormalities, butSubsequently, by using their findings, oncologists will carry out targeted therapy based on molecular classification

Keywords： molecular classification     precision medicine     pembrolizumab     PD-1/PD-L1     MSI-H    

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Title Author Date Type Operation

Multi-class dynamic network traffic flow propagation model with physical queues

Yanfeng LI, Jun LI

Journal Article

Identification of thermal error in a feed system based on multi-class LS-SVM

Chao JIN, Bo WU, Youmin HU, Yao CHENG

Journal Article

Side-channel attacks and learning-vector quantization

Ehsan SAEEDI, Yinan KONG, Md. Selim HOSSAIN

Journal Article

Max-margin basedBayesian classifier

Tao-cheng HU,Jin-hui YU

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

Supervised topic models with weighted words: multi-label document classification

Yue-peng ZOU, Ji-hong OUYANG, Xi-ming LI

Journal Article

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumerelectrical appliances classification

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

Journal Article

An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning andunary classification

Journal Article

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

Journal Article

A survey of instantaneous poles for a class of two-degree-of-freedom spherical mechanisms

Soheil ZARKANDI

Journal Article

Unified cycle model of a class of internal combustion engines and their optimum performance characteristics

Shiyan ZHENG

Journal Article

Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

Journal Article

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

Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

Yingyan Yu

Journal Article