Robotics & Machine Learning Daily News2024,Issue(Sep.5) :35-36.

Data on Support Vector Machines Reported by Researchers at Yanshan University (I mproved Pso-svm-based Fault Diagnosis Algorithm for Wind Power Converter)

Robotics & Machine Learning Daily News2024,Issue(Sep.5) :35-36.

Data on Support Vector Machines Reported by Researchers at Yanshan University (I mproved Pso-svm-based Fault Diagnosis Algorithm for Wind Power Converter)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators publish new report on Machine Learn ing - Support Vector Machines. Accordingto news reporting out of Qinhuangdao, P eople’s Republic of China, by NewsRx editors, research stated,“Due to the compl exity of the working environment of wind power generation systems, wind turbine powerconverters (WPC) can experience different types of faults. Traditional fau lt diagnosis methods suffer fromissues such as the need for additional hardware , low accuracy, long execution time, and applicability onlyto small sample offl ine fault diagnosis.”

Key words

Qinhuangdao/People’s Republic of China/Asia/Algorithms/Machine Learning/Support Vector Machines/Yanshan University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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