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Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2019.107132
Abstract: Abstract A multi-ensemble method is proposed based on deep auto-encoder (DAE) for fault diagnosis of rolling bearings. At first, several DAEs with different activation functions are trained to obtain different types of features, which are…
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Keywords:
multi ensemble;
ensemble method;
diagnosis;
fault diagnosis ... See more keywords
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Published in 2019 at "Chinese Journal of Electronics"
DOI: 10.1049/cje.2019.03.019
Abstract: The prevalence of deep learning has inspired innovations in numerous research fields including community detection, a cornerstone in the advancement of complex networks. We propose a novel community detection algorithm called the Deep auto-encoded clustering…
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Keywords:
community;
complex networks;
community detection;
algorithm ... See more keywords
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Published in 2021 at "IETE Journal of Research"
DOI: 10.1080/03772063.2021.1958075
Abstract: Nowadays, cervical cancer has emerged as one of the major causes of death and thus makes it incredibly difficult to identify it. In this research, three novel methods have been developed for the au...
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Keywords:
extreme learning;
auto encoder;
learning system;
encoder based ... See more keywords
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Published in 2020 at "Shock and Vibration"
DOI: 10.1155/2020/8891905
Abstract: To enhance the performance of deep auto-encoder (AE) under complex working conditions, a novel deep auto-encoder network method for rolling bearing fault diagnosis is proposed in this paper. First, multiscale analysis is adopted to extract…
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Keywords:
auto;
auto encoder;
method;
rolling bearing ... See more keywords