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Kernel Local Fuzzy Clustering Margin Fisher Discriminant Method Faced on Fault Diagnosis

Guangbin Wang, Xuejun Li, KuangFang He
2011 Journal of Software  
In order to better identify the fault of rotor system,one new method based on local fuzzy clustering margin fisher discriminant (LFCMFD) was proposed.  ...  magin fisher discriminant function, found optimal fault diagnosis vector,and then identified the fault class of new testing data by this vector.  ...  local fuzzy clustering margin fisher discriminant fualt diagnosis method.  ... 
doi:10.4304/jsw.6.10.1993-2000 fatcat:t2an7rc3brbjblaswhojqns4nq

Performance Enhancement of Machine Fault Diagnosis System using Feature Mapping, Normalization and Decision Fusion

Sreekumar KT, Kuruvachan K George, Santhosh Kumar C, Ramachandran I
2019 IET Science, Measurement & Technology  
Furthermore, to make the fault diagnosis system independent of speed, locality constrained linear coding (LLC), Fisher vector encoding (FVE) and mean and variance normalisation (MVN) are used.  ...  Entropy-based feature selection algorithm is proposed to improve the performance of the fault diagnosis system.  ...  [22] proposed a zSlices-Based General Type-2 fuzzy fusion method to improve the performance of bearing fault diagnosis.  ... 
doi:10.1049/iet-smt.2019.0072 fatcat:subsn7abd5cxtadkchmhaelnfm

A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: shallow and deep learning

Moussa Hamadache, Joon Ha Jung, Jungho Park, Byeng D. Youn
2019 JMST Advances  
Finally, deep-learning approaches for fault detection, diagnosis, and prognosis for REB are comprehensively reviewed.  ...  The objective of this paper is to present a comprehensive review of the contemporary techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs).  ...  [89] , a novel fault diagnosis method based on semisupervised fuzzy C-means (SFCM) cluster analysis was developed; and more recently, targeting the nonstationary and non-Gaussian characteristics of a  ... 
doi:10.1007/s42791-019-0016-y fatcat:sb3armogsvdebmwxjgpzfxwgju

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Md Khaled Hasan, Md. Shamim Ahsan, Abdullah-Al-Mamun, S. H. Shah Newaz, Gyu Myoung Lee
2021 Electronics  
This paper aims at providing fourfold discussions on face detection algorithms.  ...  Face detection, which is an effortless task for humans, is complex to perform on machines.  ...  [135] proposed two extended versions of the AdaBoost-based fault diagnosis system. One version, named gentle AdaBoost, was employed in fault diagnosis for the first time by Peng et al.  ... 
doi:10.3390/electronics10192354 fatcat:oy7adwj6cjefnm66cn5kxrybni

Kernel Association for Classification and Prediction: A Survey

Yuichi Motai
2015 IEEE Transactions on Neural Networks and Learning Systems  
Index Terms-Kernel methods, Mercer kernels, neural network (NN), principal component analysis (PCA), support vector machine (SVM). I.  ...  INTRODUCTION K ERNEL methods have been widely studied for pattern classification and multidomain association tasks [1]-[3].  ...  [110] extend Fisher discriminant analysis to associate kernel methods by incorporating KPCA and Fisher LDA.  ... 
doi:10.1109/tnnls.2014.2333664 pmid:25029489 fatcat:cotcvbtpk5fcpkwgwpg26b6clu

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
Data-Driven Fault Diagnosis Using Deep Canonical Variate Analysis and Fisher Discriminant Analysis.  ...  ., +, TII July 2021 4827-4836 Data-Driven Fault Diagnosis Using Deep Canonical Variate Analysis and Fisher Discriminant Analysis.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

Extreme Learning Machine for Thyroid Nodule Classification with Graph Cluster Ant Colony Optimization based Feature Selection

2019 International journal of recent technology and engineering  
From the experimental results, it is revealed that the proposed method is significantly better than the existing methods.  ...  In this paper, GraphClustering Ant Colony Optimization based Extreme Learning Machine approach is proposed to achieve efficient diagnosis of thyroid nodules.  ...  Firstly, the discriminate features are partitioned from the dataset using Graph Clustering based Ant Colony Optimization feature selection method.  ... 
doi:10.35940/ijrte.b2115.078219 fatcat:y24xlwkz6nf63bktouimkloptm

A review of novelty detection

Marco A.F. Pimentel, David A. Clifton, Lei Clifton, Lionel Tarassenko
2014 Signal Processing  
Roth [294, 295] propose the one-class kernel Fisher discriminant classifier to overcome the "main conceptual shortcoming" of one-class SVM classifiers, which is that the expected fraction of outliers  ...  This network was applied to different tasks, including robot sonar scans, medical diagnosis, and machine fault detection.  ... 
doi:10.1016/j.sigpro.2013.12.026 fatcat:ha6kc4bzhbajxbo2mdyh5cw5hu

2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31

2020 IEEE Transactions on Neural Networks and Learning Systems  
., +, TNNLS April 2020 1363-1374 Fault Diagnosis of Complex Processes Using Sparse Kernel Local Fisher Discriminant Analysis.  ...  Ienco, D., +, TNNLS Nov. 2020 5014-5020 Fault Diagnosis of Complex Processes Using Sparse Kernel Local Fisher Discriminant Analysis.  ...  ., +, 559-573 Joint Principal Component and Discriminant Analysis for Dimensionality Reduction.  ... 
doi:10.1109/tnnls.2020.3045307 fatcat:34qoykdtarewhdscxqj5jvovqy

Probabilistic Twin Support Vector Machine for Solving Unclassifiable Region Problem

2022 International Journal of Engineering  
For showing the superiority of our proposed method, we have conducted experiments on various UCI datasets.  ...  The proposed algorithm introduces continuous and probabilistic outputs over the model obtained by Least-Square Twin Support Vector Machine (LS-TSVM) method with both linear and polynomial kernel functions  ...  The proposed fuzzy classifier is robust to the class label perturbation and have been applied in the medical diagnosis.  ... 
doi:10.5829/ije.2022.35.01a.01 fatcat:czscjxomu5bdxfm3iercuhs6cu

Intelligent Computing Techniques for the Detection of Sleep Disorders: A Review

Vijay KumarGarg, R.K. Bansal
2015 International Journal of Computer Applications  
The most common diagnostic methods used by many researchers are based on knowledge-based system (KBS), rule based reasoning (RBR), case based reasoning (CBR), fuzzy logic (FL), artificial neural network  ...  This paper is based on the review of various intelligent computing methods that are used to detect sleep disorders.  ...  RBF networks are successfully applied for fault detection, face recognition or medical diagnosis.  ... 
doi:10.5120/19283-0701 fatcat:347gp5minzbcrdvgbiyhgjwdwy

Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review With Special Focus on Data-Driven Methods

Xingang Zhao, Junyung Kim, Kyle Warns, Xinyan Wang, Pradeep Ramuhalli, Sacit Cetiner, Hyun Gook Kang, Michael Golay
2021 Frontiers in Energy Research  
This paper provides an updated method-centric review of the full PHM suite in NPPs focusing on data-driven methods and advances since the last major survey article was published in 2015.  ...  The NPP equipment PHM is one area where the application of these algorithmic advances can significantly improve the ability to perform asset management.  ...  Du et al. (2020) proposed a self-organizing fuzzy logic classifier based on the harmonic mean difference for application in bearing fault diagnosis.  ... 
doi:10.3389/fenrg.2021.696785 fatcat:4x4pgevfsrbhrihmdsrdegyptu

Transmission Line Fault-Cause Identification Based on Hierarchical Multiview Feature Selection

Shengchao Jian, Xiangang Peng, Haoliang Yuan, Chun Sing Lai, Loi Lei Lai
2021 Applied Sciences  
To enhance the discriminant ability of the model, an ε-dragging technique is introduced to enlarge the boundary between different classes.  ...  Fault-cause identification plays a significant role in transmission line maintenance and fault disposal.  ...  Traditional fault diagnosis technologies concerning fault detecting, fault locating, and phase selection are well developed [1, 2] , while diagnosis on external causes is still underdeveloped.  ... 
doi:10.3390/app11177804 fatcat:zscbicnuvfhnpfhbhwrroik5bu

A Review of Data Mining Applications in Semiconductor Manufacturing

Pedro Espadinha-Cruz, Radu Godina, Eduardo M. G. Rodrigues
2021 Processes  
diagnosis system that relies on denoising and clustering methods for identifying spatial defect patterns in semiconductor manufacturing processes Integrated clustering scheme combining fuzzy C means (  ...  A spatial defect diagnosis system at the probing test which estimates number of clusters in advance and separates both convex and non-convex defect clusters Decision trees, a method merging entropy fuzzy  ... 
doi:10.3390/pr9020305 fatcat:jyxg4mt3gvbahnu3snh4i3rxvm

Batch Mode Active Learning for Multimedia Pattern Recognition

Shayok Chakraborty, Vineeth Balasubramanian, Sethuraman Panchanathan
2012 2012 IEEE International Symposium on Multimedia  
It is evident that our algorithm surpasses the discriminative approach by a considerable margin in terms of the running time.  ...  The Most Uncertain and Fisher methods perform better than random sampling, but are not as good as the proposed algorithms.  ...  Similarly, g 2 is always negative, g 3 is always positive, and so on.  ... 
doi:10.1109/ism.2012.101 dblp:conf/ism/ChakrabortyBP12 fatcat:kvr4sjlulrcv5cdwtrapadskm4
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