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An Efficient Rolling Bearing Fault Diagnosis Method Based on Spark and Improved Random Forest Algorithm

The random forest (RF) algorithm is a typical representative of ensemble learning, which is widely used in rolling bearing fault diagnosis. In order to solve the problems of slower diagnosis speed and repeated voting of traditional RF algorithm in rolling bearing fault diagnosis under the big data e...

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Principais autores: Lanjun Wan, Kun Gong, Gen Zhang, Xinpan Yuan, Changyun Li, Xiaojun Deng
Formato: Artigo
Idioma:Inglês
Publicado: IEEE 2021-01-01
Series:IEEE Access
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Acceso en liña:https://ieeexplore.ieee.org/document/9369361/
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