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-means clustering 1

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Afeature selection approach based on a similarity measure for software defect prediction Article

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1744-1753 doi: 10.1631/FITEE.1601322

Abstract: To fully measure the correlation between different features and the class, we present a feature selectionFirst, the feature weights are updated according to the similarity of samples in different classes.Second, a feature ranking list is generated by sorting the feature weights in descending order, and allfeature subsets are selected from the feature ranking list in sequence.Finally, all feature subsets are evaluated on a k-nearest neighbor (KNN) model and measured by an area

Keywords： Software defect prediction     Feature selection     Similarity measure     Feature weights     Feature ranking list    

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Negative weights in network time model

Zoltán A. VATTAI, Levente MÁLYUSZ

Frontiers of Engineering Management 2022, Volume 9, Issue 2,   Pages 268-280 doi: 10.1007/s42524-020-0109-1

Abstract: Monsieur Roy and John Fondahl implicitly introduced negative weights into network techniques to representpaper aims to review the theoretical possibilities and technical interpretations (and use) of negative weights

Keywords： graph technique     network technique     construction management     scheduling    

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Balancing method without trial weights for rotor systems based on similitude scale model

Ruiduo YE, Liping WANG, Xiaojie HOU, Zhong LUO, Qingkai HAN

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 4,   Pages 571-580 doi: 10.1007/s11465-018-0478-x

Abstract:

A balancing method without trial weights based on the dynamic similitude scale model was proposedThe balancing method without trial weights was proposed based on the similitude relationship of the influenceThe effect of the balancing method without trial weights was compared with that of the traditional influence

Keywords： rotor system     dynamic similitude     balancing     without trial weights     influence coefficient    

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Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 829-839 doi: 10.1007/s11465-021-0652-4

Abstract: this problem, an imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph featureeffectively achieve rotating machinery fault diagnosis towards imbalanced training dataset through graph feature

Keywords： imbalanced fault diagnosis     graph feature learning     rotating machinery     autoencoder    

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Weights-Based Gravity Energy Storage Looks to Scale Up

Sean O´Neill

Engineering 2022, Volume 14, Issue 7,   Pages 3-6 doi: 10.1016/j.eng.2022.05.007

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Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

Frontiers in Energy 2020, Volume 14, Issue 4,   Pages 817-835 doi: 10.1007/s11708-020-0709-9

Abstract: dynamic operating data set with steep slope signals is created based on physics equations and then a featuresimilarity-based learning model with an encoder and a decoder is built and trained to achieve feature

Keywords： gas turbine     dynamic simulation     data-driven     transfer learning     feature similarity    

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Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0737-8

Abstract: This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPsThe weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchyThe measured average sampling surface roughness of the most crucial feature of the bracket in the original

Keywords： selective laser melting (SLM)     build orientation determination     multi-feature mechanical part (MFMP)    

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Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 38-42

Abstract: It can extract nonlinear feature components of samples.However, feature extraction for one sample requires that kernel functions between training samples andSo, the size of training sample set affects the efficiency of feature extraction.It is supposed that in feature space the eigenvectors may be linearly expressed by a part of trainingIKPCA extracts feature components of one sample efficiently, only based on kernel functions between nodes

Keywords： KPCA(Kernel PCA)     IKPCA(Improved KPCA)     feature extraction     feature space    

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composition differences between processed protein from different animal species by self-organizing feature

Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

Frontiers of Agricultural Science and Engineering 2016, Volume 3, Issue 2,   Pages 171-179 doi: 10.15302/J-FASE-2016095

Abstract: In this study, self-organizing feature maps (SOFM) were used to visualize amino acid composition of fish

Keywords： self-organizing feature maps     visualization     processed animal proteins (PAPs)     amino acid    

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Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 406-419 doi: 10.1007/s11465-017-0419-0

Abstract: several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault featureAiming to extract the fault feature of planet gear effectively, we propose a novel feature extractioncollected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature

Keywords： wind turbine     planet gear fault     feature extraction     spectral kurtosis     time wavelet energy spectrum    

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Speech emotion recognitionwith unsupervised feature learning

Zheng-wei HUANG,Wen-tao XUE,Qi-rong MAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 5,   Pages 358-366 doi: 10.1631/FITEE.1400323

Abstract: In this paper, we apply several unsupervised feature learning algorithms (including -means clustering

Keywords： Speech emotion recognition     Unsupervised feature learning     Neural network     Affect computing    

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

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

Abstract: Therefore, a fault detection method based on self-supervised feature learning was proposed to addressA comprehensive comparison study was also conducted with various feature extractors and unary classifiersmodel can detect progressive faults very quickly and achieve improved results for comparison without feature

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

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Application of wavelet scalogram in feature extraction of acoustic emission signal

Xiao Siwen,Liao Chuanjun,Li Xuejun

Strategic Study of CAE 2008, Volume 10, Issue 11,   Pages 69-75

Abstract: By analyzing the characteristics and feature extraction of typical AE signals, the paper applies wavelet

Keywords： wavelets scalogram     acoustic emission     feature extraction     fault diagnosis     rolling bearing    

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A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Strategic Study of CAE 2006, Volume 8, Issue 8,   Pages 50-55

Abstract: Then the fusion features in the complex feature space is extracted by using complex PCA (CPCA).

Keywords： feature fusion     linear discriminant analysis (LDA)     feature extraction     face recognition    

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Feature selection techniques for microarray datasets: a comprehensive review, taxonomy, and future directions Review

Kulanthaivel BALAKRISHNAN, Ramasamy DHANALAKSHMI,bala.k.btech@gmail.com,r_dhanalakshmi@yahoo.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 10,   Pages 1451-1478 doi: 10.1631/FITEE.2100569

Abstract:

For optimal results, retrieving a relevant feature from a has become a hot topic for researchers involvedway for comprehending and highlighting the multitude of challenges and issues in finding the optimal featureaccuracy and convergence ability of several wrappers and hybrid algorithms to identify the optimal feature

Keywords： Feature selection     High dimensionality     Learning techniques     Microarray dataset    

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Title Author Date Type Operation

Afeature selection approach based on a similarity measure for software defect prediction

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Journal Article

Negative weights in network time model

Zoltán A. VATTAI, Levente MÁLYUSZ

Journal Article

Balancing method without trial weights for rotor systems based on similitude scale model

Ruiduo YE, Liping WANG, Xiaojie HOU, Zhong LUO, Qingkai HAN

Journal Article

Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning

Journal Article

Weights-Based Gravity Energy Storage Looks to Scale Up

Sean O´Neill

Journal Article

Dynamic simulation of gas turbines via feature similarity-based transfer learning

Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG

Journal Article

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective

Journal Article

Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Journal Article

composition differences between processed protein from different animal species by self-organizing feature

Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

Journal Article

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet

Yun KONG, Tianyang WANG, Zheng LI, Fulei CHU

Journal Article

Speech emotion recognitionwith unsupervised feature learning

Zheng-wei HUANG,Wen-tao XUE,Qi-rong MAO

Journal Article

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

Journal Article

Application of wavelet scalogram in feature extraction of acoustic emission signal

Xiao Siwen,Liao Chuanjun,Li Xuejun

Journal Article

A Face Recognition Based on Fusion Features Extraction From Two Kinds of Projection

Zhang Shengliang,Xu Yong,Yang Jian,Yang Jingyu

Journal Article

Feature selection techniques for microarray datasets: a comprehensive review, taxonomy, and future directions

Kulanthaivel BALAKRISHNAN, Ramasamy DHANALAKSHMI,bala.k.btech@gmail.com,r_dhanalakshmi@yahoo.com

Journal Article