Research Data from Shanghai Maritime University Update Understanding of Support Vector Machines (Rolling bearing fault diagnosis based on fine-grained multi-sca le Kolmogorov entropy and WOA-MSVM)

Robotics & Machine Learning Daily News2024，Issue(Mar.28) ：18-18.

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Research Data from Shanghai Maritime University Update Understanding of Support Vector Machines (Rolling bearing fault diagnosis based on fine-grained multi-sca le Kolmogorov entropy and WOA-MSVM)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in . Accor ding to news originating from Shanghai, People's Republic of China, by NewsRx ed itors, the research stated, “In allusion to solve the issue of fault diagnosis f or bearing and other rotatory machinery, a technique based on fined-grained mult i-scale Kolmogorov entropy and whale optimized multi-class support vector machin e (abbreviated as FGMKE-WOA-MSVM) is proposed.”

Key words

Shanghai Maritime University/Shanghai/People's Republic of China/Asia/Emerging Technologies/Machine Learning/Suppo rt Vector Machines/Vector Machines

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出版年

2024

Robotics & Machine Learning Daily News

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