Importance of the attributes of fan No.15.

<div><p>The icing failures of wind turbine blades are critical factors that affect both power generation efficiency and safety. To improve the diagnostic accuracy and speed, an improved weighted kernel extreme learning machine (IWKELM) optimized by multi-strategy adaptive coati optimizat...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Xingtao Wu (22139242) (author)
مؤلفون آخرون:	Yunfei Ding (13570771) (author), Ruizhi Zhao (225982) (author), Dong Ding (112949) (author), Hongwei Zhang (28335) (author), Lin Wang (11986) (author)
منشور في:	2025
الموضوعات:	Medicine Biotechnology Cancer Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified wind turbine blades strategy adaptive coa real scada data power generation efficiency improved objective function dimensionality reduction technique model optimization performance e ., macoa icing diagnostic model accuracy reaches 92 diagnostic model icing failures diagnostic accuracy xlink "> vy flights two sets standard deviation random forest internal distribution critical factors case study
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Importance of the attributes of fan No.15.

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