首页|Studies from Guangxi University Yield New Information about Machine Learning (Machine Learning-based Non-destructive Testing Model for High Precision and Stable Evaluation of Mechanical Properties In Bamboo-wood Composites)
Studies from Guangxi University Yield New Information about Machine Learning (Machine Learning-based Non-destructive Testing Model for High Precision and Stable Evaluation of Mechanical Properties In Bamboo-wood Composites)
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
Springer Nature
Investigators publish new report on Machine Learning. According to news reporting from Guangxi, People's Republic of China, by NewsRx journalists, research stated, "The efficient evaluation of mechanical performance of bamboo-wood composites (BWCs) is an important part for their development and application. To address the issues of low efficiency, high consumables usage, and low accuracy in traditional BWC mechanical performance testing, a non-destructive testing method for BWC mechanical performance was proposed based on machine learning." Funders for this research include National Natural Science Foundation of China (NSFC), Guangxi Science and Technology Base and Talent Special Project, Sichuan University.
GuangxiPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningGuangxi University
NETL
NSTL
Springer Nature
