首页|Data from Science University of Malaysia Advance Knowledge in Machine Learning ( Real-time Leakage Predictions of Pneumatic Controlled Actuator During Cycle Test Using Machine Learning)
Data from Science University of Malaysia Advance Knowledge in Machine Learning ( Real-time Leakage Predictions of Pneumatic Controlled Actuator During Cycle Test Using Machine Learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting from Penang, Malaysia, by NewsRx journali sts, research stated, “The pressure decaying test is traditionally used to detec t leakage in pneumatic actuators; however, it is time-consuming as it is perform ed between cycles of actuation. To date, there is a notable lack of real-time, d ata-driven machine learning methods to detect such leakages.”
PenangMalaysiaAsiaCyborgsEmergin g TechnologiesMachine LearningScience University of Malaysia
NETL
NSTL
