首页|New Findings from Semnan University in the Area of Machine Learning Published (Shapley additive explanation on machine learning predictions of fatigue lifetimes in piston aluminum alloys under different manufacturing and loading conditions)
New Findings from Semnan University in the Area of Machine Learning Published (Shapley additive explanation on machine learning predictions of fatigue lifetimes in piston aluminum alloys under different manufacturing and loading conditions)
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-Current study results on artificial in telligence have been published. According to news originating from Semnan, Iran, by NewsRx correspondents, research stated, “Various input variables, including corrosion time, fretting force, stress, lubrication, heat-treating, and nano-par ticles, were evaluated by modeling of stress-controlled fatigue lifetimes in AlS i12CuNiMg aluminum alloy of the engine pistons with different machine learning ( ML) techniques.”
NETL
NSTL
