首页|Ternopil Ivan Puluj National Technical University Researcher Describes Advances in Machine Learning (Loading Frequency Classification in Shape Memory Alloys: A Machine Learning Approach)
Ternopil Ivan Puluj National Technical University Researcher Describes Advances in Machine Learning (Loading Frequency Classification in Shape Memory Alloys: A Machine Learning Approach)
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 DailyNews Daily News – New study results on artificial intell igence have been published. According to newsoriginating from Ternopil, Ukraine , by NewsRx editors, the research stated, “This paper investigates theuse of ma chine learning methods to predict the loading frequency of shape memory alloys ( SMAs) basedon experimental data. SMAs, in particular nickel-titanium (NiTi) all oys, have unique properties thatrestore the original shape after significant de formation.”
Ternopil Ivan Puluj National Technical U niversityTernopilUkraineEuropeAlloysCyborgsEmerging TechnologiesMa chine Learning
NETL
NSTL
