Application of independent component analysis with semi‐supervised Laplacian regularization kernel density estimation
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DOI: 10.1002/cjce.23067
Abstract: In this study, fault detection and fault reconstruction methods are developed using matrix factorization of component vectors obtained with independent component analysis (ICA). Two monitoring statistics are used for fault detection in a detailed analysis… read more here.
Keywords: fault; independent component; semi supervised; analysis ... See more keywords
Multiple Instance Learning via Semi-supervised Laplacian TSVM
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DOI: 10.1007/s11063-017-9579-5
Abstract: Multiple instance learning attempts to learn from a training set consists of labeled bags each containing many unlabeled instances. In previous works, most existing algorithms mainly pay attention to the ‘most positive’ instance in each… read more here.
Keywords: instance learning; semi supervised; multiple instance; via semi ... See more keywords
Nonlinear machine fault detection by semi-supervised Laplacian Eigenmaps
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DOI: 10.1007/s12206-017-0712-1
Abstract: A semi-supervised Laplacian Eigenmaps algorithm for machine fault detection is proposed. The purpose of the algorithm is to efficiently extract the manifold geometric characteristics of nonlinear vibration signal samples, and to determine fault classification of… read more here.
Keywords: fault; semi supervised; fault detection; laplacian eigenmaps ... See more keywords